Sunday, 25 January 2015

Field Marks - Shaft-streaks and Tramlines

Of all the typical patterns found on feathers, shaft-streaks can be among the most subtle.  And yet, such a simple pattern may be all that is needed to create a complex and effective camouflage.  If the feather shaft or rachis contrasts with the surrounding feather barbs, the rachis itself forms a very fine shaft-streak.  Such subtle markings are rarely detectable in the field.  However, add even the faintest, diffuse pigmentation along the edges of the rachis and we now have shaft-streaking which we can actually see, perhaps even at long range.

When we combine these marks with the typical anatomy of a bird (HERE) we start to see complex yet consistent patterns emerge.  Feather patterns as subtle as these allow a bird to blend with its surroundings to evade detection by predators.  Wherever feathers run in consistent lines these fine marks begin to aggregate into more prominent features such as crown streaks and 'tramlines' on the mantle.  Wherever feathers are less perfectly aligned, these marks are often far less prominent and appear as finer streaks.  The problem of course, is that these aggregate field marks (eg. tramlines) are subject to a bird's posture and may quickly vanish if feathers are not aligned perfectly.  Under such circumstances a bird may appear unrecognizable.

This image of a Buff-bellied Pipit (Anthus rubescens) illustrates a lot of the subtle points relevant to this discussion.  On the scapulars there are some very subtle diffuse shaft streaks.  One would have to look very closely to pick out any dark pigmentation in the centre of these feathers.  At range these feathers are going to look uniform.  On the crown, mantle and flank the shaft streaks are more prominent, but note how much more prominent the streaking is where the feathers are neatly aligned, such as on the crown and mantle.  The streaks on the upper flank tend to be more dispersed.  I have attempted to illustrate these points more clearly below.

In order for shaft-streaks to aggregate into larger marks the streaks must reach the feather tip and of course the feathers need to align perfectly.  This approach works best on the upperparts and is more hit-and-miss on the underparts, owing to the greater size, downiness and mobility of underparts feathers.  I guess if, as a bird your concern is typically a bird of prey quartering overhead, it is probably more important that the tight upperparts camouflage works well.

This particular Buff-bellied Pipit was joined by a second bird, remarkable in being only the 3rd and 4th Irish records at the time, but proving to be part of a significant influx of six birds in 2007 (more HERE).  As an aside, it was interesting to compare the pattern of the two birds that occurred together in Lissagriffin, Co. Cork.  One couldn't imagine two more different-looking individuals.  The four subsequent birds also differed significantly enough to be easily separable from these and one another.  Among all the intra-specific variation however the mantle pattern appeared fairly constant in these birds.  Together with the distinctive call, the fine mantle shaft-streaking has proven to be perhaps the most useful field mark for birders searching for Buff-bellied Pipits over here.  

Lighting and Composition
I have written generally about this pair before (HERE).  Lighting affects the contrast of field marks.  Shadows can easily be mistaken for streaking and some shadows consistently follow the contours of feathers (as illustrated HERE).  So what is the best lighting and composition for accurately gauging and analysing shaft-streaking?  The best viewing angle for any feature is one in which the feathers are viewed in profile, perpendicular to the line of sight and where the sun is behind the observer.  Diffuse light is far preferable to direct sunlight as contrast is less so there is a greater potential to preserve tonal range.  Tonal range is really important here, because we need a range of tone to depict the full gradient of tonal levels in a diffuse field mark.

Lighting Tools
If lighting or exposure has been less than optimal lighting tools (HERE) can help to unmask field marks that might otherwise be hidden in an image.  Shaft-streaks can be problematic however as they are often diffuse in nature, which means that they require a broader tonal range for accurate display than more clearly defined field marks.  Dynamic range limitations may obliterate these subtle gradients and similarly overuse of contrast tools, unsharp mask or other tools that impact on image contrast and tonal gradients need to be used with care.

Other Factors
Feather displacement, water and soiling can all dramatically alter the normal pattern of feathers.  We just need to be on the lookout for these and factor them in to our analysis. All of the standard image quality parameters are also at play here.  Clearly, distance from the subject is very relevant so image pixel resolution is important.  Fine detail requires high resolution, pure and simple.  Focus dissolves fine marks and reduces contrast, so subtle, diffuse pigmentation is also dissolved.  Under and over-exposure also both reduce contrast and may therefore obliterate diffuse edges of shaft-streaks.  Poor white balance introduces colour casts which again can mask subtle, diffuse patterns.  Lastly various image artefacts can either mimic or mask shaft-streaking.

In summary, shaft-streaking is a simple but highly effective means of forming complex patterns and camoflague in plumage.  In some species shaft-streaking may be an important field mark.  That field mark may consist of an individual feather streak or an aggregate of feathers in which shaft-streaks are aligned to form larger streaks or tramlines.  At a micro-level, accurate capture and analysis of shaft-streaks requires good lighting and exposure owing to the tonal range required.  All of the standard image quality parameters are at play, making this one of the most challenging field marks to accurately analyse in digital images.

Monday, 19 January 2015

Field Marks - Lighting and Bare Parts

In Birds and Light - Translucency I outlined the difference between opaque, transparent and translucent  materials.  Avian bare parts are translucent in nature, which means that a certain proportion of the light hitting a bird's bill and legs passes through those structures.  In doing so, these are illuminated internally.  This property can dramatically alter the appearance of bare parts under different circumstances.  

Take for instance the Booted Warbler (Iduna caligata) pictured below.  I twitched and photographed this confiding individual in Ballycotton, Co. Cork in early September, 2004.  It was only the second Irish record at the time and coincidentally was followed by the 3rd Irish in Co. Mayo later the same day.  The day was exceptionally mild and sunny and the bird performed well in this bright sunshine.

The sub-terminal mark on the base of the lower mandible is a relevant field mark in this species but I struggled to get any good photos of it due to the strong light.  In the main image, inset, the bird is illuminated by strong sunlight from the right as evidenced by the sun's reflection on the bird's eye and bill.  There are also shadows from twigs falling on the subject's nape and side.  The bill is brightly illuminated and it's subtle tones are somewhat obscured as a result.  The lower mandible appears to be mainly flesh-coloured.  In the smaller inset image the bird is clearly in silhouette.  The bill colour appears much different in this image, with a richer orange colour to the lower mandible.  Interestingly, the darker parts of the bill, the upper surface of the upper mandible and the sub-terminal mark on the lower mandible are much more visible in this image than in the other, better lit image.  The pattern of darker areas being subdued while lighter areas are illuminated is consistent with translucency.  Light passes through the paler areas more freely and therefore they appear brighter.  What is most interesting however is that this bright orange colouration is probably due to the colour of the bird's mouth, not it's bill.  The internal structures of translucent objects as well as their colours are illuminated by light passing through them.

Birds of the Western Palearctic (BWP) describes the colour of the bill of Booted Warbler as follows.  Upper mandible and distal half of lower mandible dark brown or brown black in caligata.  Base of lower mandible pale flesh, pale yellow, orange-flesh or orange-horn.  Mouth pale lemon-yellow, bright yellow or orange-yellow.  Note the description of the lower mandible and mouth includes the related I. rama (caligata and rama were considered conspecific when BWP was published).  

As the image above shows, the bill colouration varies dramatically due to lighting.  As stated, the bright orange colour when the bill is back-lit appears to be due mainly to internal illumination due to translucency.  The image below illustrates just how vivid orange the bird's mouth actually is.  This undoubtedly influences the colour of the bill when it is illuminated in strong light, and especially when it is viewed while being lit from behind.

These images were digiscoped with a Nikon Coolpix 4500 and Leica Televid scope.  Note the bill graphics above are only an approximation in structure, pattern and colouration, based on various photos and are used here merely to illustrate the specific point.

The legs in many birds are equally difficult to pin down in terms of pattern and colouration.  As this image shows, bright sunlight can reflect more strongly from the bare parts than from plumage, obscuring the true colour of the bare parts.  The description of the leg colour variation of Booted Warbler in BWP is too long to repeat here.  Natural variation only serves to further compound the problem posed by lighting and other environmental factors.

Remaining bare parts include the eyes and bare skin, eg. the orbital ring around the eye, wattles and facial skin in parrots and vultures.  Judging the colour of the iris and bare patches of skin is similar to judging bill and leg colour.  It depends on lighting, exposure and of course white balance.  Occasionally dark eyes may appear paler than they should be owing to a peculiar light angle in which sunlight reflects and illuminates inside the eyeball, but for the most part lighting tends to be fairly predictable.  Of course, one of the great advantages of the surface of the eye-ball is it's facility to allow us judge the sun's position more or less.  Other factors to consider here include include moisture, natural oily or waxy coatings on bare parts, soiling from earth, pollen or other foreign bodies, scaling and abrasion due to the elements, etc., etc.

I have included this close portrait of a Ring-billed Gull (Larus delawarensis) to illustrate the complex colouration within bare part structures when viewed under optimal lighting.

In summary, lighting plays a major role in how field marks are displayed, not least on bare parts.  This posting illustrates how the internal colouration of a bird's bill can actually influence it's external appearance under certain lighting conditions.  All of this compounds an already complex challenge of trying to accurately depict patterns and colours in bare parts.  One needs to be especially critical when trying to gauge colour and patterns in these areas and should not be too concerned or surprised if a field mark appears to be missing.  In all likelihood the mark is simply obscured.  As always for the best results look for the images captured under duller, more diffuse light and be wary of images captured in bright sunshine.  It's also probably best to avoid drawing strong conclusions where translucency is at play, given the potential complexity of internal structures being illuminated.

Thursday, 8 January 2015

Field Marks - Lighting and Avian Anatomy

In 2015 I am going to be focusing a lot on the identification of field mark in digital images.  In the series of postings Birds and Light I have been exploring the broader subject of lighting and it's influence on images.  For the time being I will be looking more specifically at the impact of lighting on field marks in images.

Avian Anatomy
The overall structure of objects determine how they appear when lit.  The contours of a bird are determined by it's musculoskeletal structure, overlaying skin and soft tissue, but probably most importantly of all, by the overlay of feathers covering its surface.

Feather tracts, called pterylae are areas of skin on a bird from which feathers grow.  Feathers are not located randomly on the surface of a bird but are distributed often in lines of feathers within feather tracts.  Between these feather tracts are patches of bare skin called apteria.

Just as the hairs on your hand become erect due to muscle contraction when it is cold, birds can fluff up their feathers to trap air in between as insulation from the cold.  Unlike the autonomic control of hair erection in mammals including humans, birds have considerable control over the erection and relaxation of their feathers and it's mechanism is more complex than the simple hair control in mammals (see HERE and HERE).  Many birds obviously use this adaptation in courtship.  Feathers don't raise and lower randomly but rather in lines and clusters.  There is a certain predictability in contours and patterns and the more we study birds the more familiar we become with these patterns.  Of course the movement of feathers is also influenced by the wind and some feathers are more downy than others so are more likely to remain out of position.  There is some nice detail on feathers and plumage HERE, from where the sketches of the pterylae and apteria of Clark's Nutcracker were sourced for the graphic above.  I photographed the accompanying Clark's Nutcracker in Canada in early July.

Typical Plumage Coutours
When we look at the combination of anatomy and feather tracts we start to see some consistency in the contours of birds.  Interestingly standard bird topography doesn't always coincide exactly with a bird's contours.

The Head and Neck
The head and neck of most birds tends to be well feathered (capital tract).  There often tend to be apteria encircling the eyes and from the eyes out and around the auricular region.  This might explain why the ear-covert feathers (auriculars) are bigger as they need to cover this area of bare skin, and why they are often not as neatly aligned as the crown, nape and throat feathers.  There may be other small apteria on the head and neck as for example in the submalar apterium of the Clark's Nutcracker shown above.  However, with the exception perhaps of the loral area, around the eye and the ear-coverts, the rest of the head and neck tends to be quite uniformly feathered in lines of feathers facing backwards from the bill.  Thus the forehead, crown, nape and throat feathers tend to produce fairly consistent looking shadows, consisting of narrow streaks of fine shadow running along the direction of the feathers.  Then, if feathers are raised, typically we see this as lines of transverse shadow running along the end of these parallel lines of feathers.

The Lores, Supercilium and Ear-coverts (auriculars)
The shade of the lores can represent an important fieldmark for some species and this field mark may not always be so easy to judge in a photograph.  This is due in part to the contour of the head, but also due to the complex feather arrangement in this area.  The same applies to the supercilium, eye-ring and other field-marks associated with the ear-coverts.  So we must pay attention to the fact that feather position can really influence the appearance of a field mark around the face of a bird.

Pseudo-field-marks may be due to shadow and may therefore only manifest under certain lighting conditions.  Take the supra-loral shadow in Booted Warbler (Iduna caligata), only visible when the head is angled in a certain way relative to the sun.  As the composite above shows, if this area of the head is in full sun the field mark is missing.  In this species the field mark seems to be produced by a thick or pronounced tuft of feathers on the forehead.

Throat, Breast, Belly and Vent
As the Robin image below illustrates, the throat is not a uniform shape.  The auriculars, submoustachial and throat areas all represent distinct regions within the ventral tract.  The crop is an important consideration.  If it is full, the bulge can transform the appearance of the features in this area of the bird's plumage.  As the head swivels, and depending on the posture of the neck, a shadow or cleft may form along the throat line, and depending on the posture of the neck some feathers can be partially obscured beneath throat feathers.

Another cleft is formed between the two prominent pectoralis muscles (breast muscles) connected to the prominent breast or keel bone.  There is a large apterium running down the centre of the breast and parting the ventral feather tract. This apterium further enhances this channel.  Surprisingly, standard topography does not give this cleft a name, despite the fact it is quite prominent on some birds and may even carry a distinctive field mark on some species.

As these Robin and Western Bonelli's Warbler photos illustrate, the patterning of shadow on the underside of a bird often consists of characteristic but faint longitudinal shadows running down the edges of breast and belly feathering, plus the central cleft and transverse shadows associated with the delineated throat, breast, belly and vent (not shown).  There may also be shading in the femoral tract area, delineating the edge of the rear flank (also not shown in these images).

Upperparts - Mantle, Rump and Flight Feathers
The mantle and rump feathers of many birds tend to follow the same linear pattern of near parallel rows of feathers as the crown and nape, which is convenient.  The stiff flight feathers of the wings and tail also tend to have consistent order which again makes for consistent lighting patterns.  Of course, individual feathers may be moulting or displaced and this can lead to confusion, so we can never be complacent when it comes to reading lighting and shadow on the contours of a bird.  In case you are confused by the image below it is a hummingbird feeding from a flower with it's back to the camera (Sooty-capped Hermit, Venezuela).  It's pale-edged crown, nape, mantle, and rump, tapering to rusty-coloured upper-tail coverts illustrate a consistent feather arrangement common to many birds.

Tuesday, 6 January 2015

Forensics : Gaussian Analysis - Underexposure

Scope and Objective
In An Introduction to Gaussian Analysis (HERE) I outlined how most image quality parameters exhibit a Gaussian distribution around an optimum quality standard.  This presents an opportunity to look for 'Gaussian Signatures' left behind in digital images.  Here I am analysing Gaussian signatures for underexposure.  I am looking for evidence that would indicate if data (eg. subtle field marks) may have been lost due to underexposure in an image.  I am also looking to prove the opposite - in the absence of a Gaussian signature for underexposure is it reasonable to assume that there is no loss of detail due to underexposure clipping?

The Gaussian Signatures for Underexposure
Just like overexposure, underexposure works rather like an image brightening tool and has the effect of pushing the histogram to the left (for more on histograms see HERE).  However, unlike a brightening tool which stacks detail up on the side of the histogram, underexposure, like a conveyor belt, simply pushes tonal data off the edge of the histogram (clipping).

Once again, as with overexposure, progressive underexposure causes image fine details and colours to simply vanish.  Before detail vanishes it will get progressively darker and approaches pure black in colour (sRBG R=0, G=0, B=0).  This becomes a Gaussian signature for underexposure.

However probably a far more recognisable signature for underexposure is Image Noise.  Noise can obscure fine colour and detail long before these are clipped.  There are different types of image noise as neatly outlined HERE and HERE, but typically noise is expressed in terms of Luminance noise (fluctuations in the darkness of pixels) and Chroma noise (fluctuations in the hue and saturation of pixels)   Noise is quantified in terms of a signal to noise ratio (SNR).

ISO and Noise Reduction Software
ISO is a measure of the relative sensitivity of a photographic film or image sensor to light.  It is often considered part of the exposure triangle with shutter speed and aperture.  However, ISO in digital cameras is created by amplifying an image after the exposure is made, not during image exposure.  So, in reality ISO is distinct from exposure.  Modern digital cameras exhibit incredible ISO range.  This is due mainly to the sophistication of image amplification and noise reduction software.  As the name implies, the reduction or elimination of noise involves image manipulation, so it may have the effect of masking image detail.  So it would be advisable to pay attention to the ISO of an image.  A modern camera may not suffer quite as badly from underexposure but the trade-off could be that the image has has been over-processed by the camera instead.  That said, at lower ISOs, modern cameras far exceed and produce far more accurate results than their predecessors.  It is only at really high ISOs that we need to be more mindful of this problem.  Take for example the image below.  The Nikon Coolpix 4500 was a brilliant digiscoping camera in it's day but it's image quality is relatively poor compared with modern compact digital cameras.

Note how the level of noise is proportional to the darkness of the objects being photographed.  The darker head, neck and breast is very noisy because there is very little light from these areas, reaching the sensor.  There is slightly less noise on the dark grey mantle and less again in the paler grey portion of the bill, grey flank and on on the water.  Finally we see virtually no noise at all in the white areas of the bill and breast side.  So, provided a certain threshold of light reaches the sensor the noise problem is sorted.  It is also true to say that it is possible to have patches of underexposure, normal exposure and indeed overexposure, all within the same image.

Gamma or rather Gamma Correction is of particular relevance to this discussion.  The human visual system does not discriminate between increments of brightness in a linear fashion.  Our eyes are better able to distinguish between small changes in luminance within shadows and midtones in a scene.  In the highlights, or brighter areas of a scene our eyes can only distinguish between larger incremental changes in light intensity.  This attribute partly explains why human vision has such as broad dynamic range when compared to a camera.  Gamma correction is a correction made by an image processor to transform an image from a linear luminance distribution to one that matches the human visual system.  Display devices may also have their own additional gamma correction to cancel any non-linear properties they may have be it a CRT or LCD screen.  A consequence of this is that image detail can be lost within the highlights but an advantage is that there tends to be a greater range of tones preserved in the shadows and midtones.  Automatic camera exposure tends to compensate for this by tending towards underexposure rather than overexposure in an image.  As we can see from the example above however, excessive underexposure does nothing for an image.

Underexposure is a common image quality complaint, especially when we consider the challenging conditions under which many bird images are taken.  Whereas overexposed images can be analysed for clipping, image noise often tends to be a more significant issue than clipping within underexposed images - image detail and colour is often obscured by noise long before it is ever clipped.  It helps to get the know the typical noise signature of ones own camera and to pay attention to ISO ratings and the possible overuse of noise reduction software when analysing potentially underexposed images.  If an image is well exposed with little or no noise evident we have the best conditions possible for capturing accurate details and colours.  In contrast, when we have noisy, underexposed images we always need to consider that colours and fine details may have been obscured.

Thursday, 1 January 2015

Human Bias - Ten Tips

In the last few postings I have explored a range of different human cognitive biases and arranged them into a certain order which we will hopefully find useful here.  The lists include distraction biases, evaluation biases, memory biases, biases of the self and the group and finally experimental bias.  This is not an entirely exhaustive list.  We also have various social biases and others (see HERE) which I have not looked at because we are only interested in a narrow subject and context.  

The Context
Essentially our context is typically one where we are quietly examining one or more digital images, possibly with some additional supportive notes.  Whereas during field observation, where we may find ourselves making split-second decisions, we should not be under any great time pressure to make a critical evaluation from a set of digital images (unless perhaps the photos are part of a table quiz).  Our main distractions are likely to lie within the evidence itself.  We find ourselves evaluating the available evidence, drawing on our own knowledge and memory to do so (hopefully with access to research materials if needed).  We may be feeling we need to justify our conclusions to our peers, possibly even publishing them to the world over the internet.  So a great many of the common cognitive biases will still apply, but often in a setting where if we wish we can apply control over bias.  So what are we looking for and how do we avoid bias?

In earlier postings I have made some comparisons between the human visual system and the camera (HERE and HERE).  During critical observation our focus is extremely narrow.  If I allow my judgement to guide my line of observation I can very easily miss something right under my nose.  We know that we have a tendency to anchor on certain details.  Consider how differently we would view the below image (mystery diver, Gavia sp.) if we had first read just one of these two observer notes.

Observer 1
A medium-sized diver with a prominent dark neck strap, clearly visible throughout the observation...

Observer 2
A large diver, viewed distantly in choppy waters.  Appeared to have a neck strap but difficult to make out due to the strong shadow and low light...

If we want to avoid being distracted we must try and clear the mind and quell any prior expectations we may have.  We must also try and approach the puzzle in a logical and systematic fashion, reserving all judgements until we have reviewed all of the available evidence.  With images we have the opportunity to look at an identification with a fresh pair of eyes.  I would advise pushing all the other information aside and concentrating on identification from first principals from the images before introducing additional information from the available notes.  A full analysis of a photo could take some time and objective analysis deserves that investment, because once additional information is introduced to the analysis it begins to alter our perceptions.  I would take each photo as though it were in isolation and extract every available detail from it before moving on.  I would also recommend taking detailed notes for each image.  Memory is fickle and an important observation can be forgotten or twisted by bias to suit a new perception. 

To evaluate anything we need to understand the limits of the subject, so we need a set of assessment criteria.  When it comes to identification of a bird from photos we are not just referring to the criteria used to separate one species from another.  We also must consider the criteria for accurately judging details and colour from images.  This requires a good understanding of how images are created and the reliability of different criteria when viewed in digital images.  As we have seen, there are a lot of variables to consider so we must take our time and challenge each of our own conclusions very carefully. 

Continuing with the above diver example we must remember that we begin to make evaluations from the very moment we receive sensory information.  As we have seen, a range of biases actually help guide our judgement and can quickly lead us astray.  We need to keep an open mind and try to avoid investing in one answer at the expense of another.  We must also try and be as critical as we can be of our own findings and try and approach each question equally from both sides of the argument.  It might be worth imagining having to debate the more convenient side of the argument and then having to present the alternative, apparently less-likely side with even greater conviction, as though it were the correct answer.  In order to do so, it is likely every conclusion will have to be rigorously challenged.

This mystery diver is a tough call.  With only one available image all attempts to improve on the original JPEG (left) have only yielded a slightly better quality image (right).  If we have avoided all distractions and resolved all the available evidence from this image we should have concluded that the image is ambiguous at best.  

We know that as humans we all suffer from cognitive bias so we cannot apply the same level of objectivity to written descriptions as we can to digital images.  We have to allow for the possibility that a written description is factually inaccurate, no matter how careful the observer has been.  If we make the conscious decision not to accept what we read as fact, then what is our starting position?  I would advocate that we create two opposing positions and argue both of them based on the evidence.  If we cannot satisfy ourselves that one argument wins out firmly over the other then it is probably safe to say that the evidence is inadequate to support a firm identification.

As someone evaluating the information we must draw on our own memory and understanding of the limits of the subject.  There are a lot of variables to consider so we may forget to apply certain tests or come at the puzzle misinformed.  It pays to have lists as an aide-mémoire.  We might list the identification criteria for a particular species and the sources where those criteria can be found.  We might use a standard list of image quality parameters and a list of image tests and modifications we can choose from to test or extract evidence from images.

Biases of the Self and the Group
It is possible to be influenced by the group and influenced by various ego-driven biases.  The more structured the analytical process is the greater the chance of avoiding these pitfalls.  It is best to conduct one's own analysis prior to reviewing the analysis of others.

Experimental Bias
If analysis involves conducting an experiment or experimenting with images to try and resolve a question, it is important to set objectives and maintain an open mind.  It is possible to be overly selective and to only apply direct testing, thereby narrowing the focus and ignoring other possible solutions.

Ten Tips
Here are some general findings from this initial analysis of different forms of cognitive bias.

(1) Try and approach all identifications with an open mind, free from preconceptions and distractions.
(2) Start with the images first.  Treat each image as though it were the only image available and give it the full attention it requires.  Take notes as memory can be fickle.
(3) When evaluating evidence consider a counter-argument for each conclusion and try and build a strong case for both sides of an argument.
(4) When reviewing observer notes always assume that they are biased and therefore factually may be full of inaccuracies.
(5) Start from the most conservative position and work up to an answer based on a logical foundation of evidence.
(6) Avoid relying too much on one's own memory.  Work systematically using lists of identification criteria, lists of image quality parameters and artefacts.
(7) Try not be get too invested in the outcome.  Focus on the analysis.
(8) You are under no pressure to publish your findings or put them up for peer review.
(9) Wait until you have completed your own analysis before reviewing the analysis of others.
(10) If you are experimenting with images or generating experiments to test a theory try to avoid narrow, direct forms of testing.

It is my intention to develop these ideas further and start to produce some general tools to minimise bias during analysis.

Human Bias - Experimental

Scientific method relies on the design of sound experiments and the presentation of results that can be verified and replicated by others.  Experimenter's or expectation bias is the tendency for experimenters to believe, certify and publish data that agree with their expectations for the outcome of an experiment, and to disbelieve, discard or downgrade the corresponding weightings for data that appear to conflict with those expectations.  The observer-expectancy effect occurs when a researcher expects a given result and therefore unconsciously manipulates an experiment or misinterprets data in order to find it.  Selection bias is the distortion of a statistical analysis, resulting from the method of collecting samples.  If data is selected appropriately the results and conclusions will be false or misleading.  Insensitivity to sample size is the tendency to under-expect variation in small samples.  The less-is-better effect is a preference reversal where a dominated smaller set is preferred to a larger set.  

The congruence bias is the tendency to test hypothesis exclusively through direct testing, instead of testing possible alternative hypothesis.  Conjunction fallacy is the tendency to assume that specific conditions are more valid than general ones.  Outcome bias is the tendency to judge a decision by its eventual outcome instead of based on the quality of the decision at the time it was made.  Pro-innovation bias is the tendency to reflect an excessive optimism towards an invention or innovation, failing to identify weaknesses or address the possibility of failure.

For more see HERE.