"size" ignores features much larger than the typical pellet size. If a conventional pattern plate target with a bulls-eye and pre-marked segments is scanned-in, the "size" setting can suppress these features of the target.
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Decrease / increase the size of the image. Does not affect
pellet detection. |
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Block a small, medium or large area of the image from automatic
pellet detection. Manually added pellets are unaffected. (see on-screen Blocked
Area) |
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Set active area button. Drag the boxes at the top-left and bottom-right
to set the area that will be scanned for pellet holes. |
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Adjust the slider to set the automatic pellet detection level and give the best balance between not detecting true pellet marks and false pellet detection when the contrast between the pellet marks and background is poor. False detection can be blocked manually. Undetected pellets can be added manually. |
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Set the scale of the image. Drag the
up/down arrows on the image
to indicate a known vertical distance on the image and the left/right
arrows to indicate a known horizontal distance. Move the graticule to
indicate the point of aim. |
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"double" is used to detect near-coincident pellet strikes.
(NB this feature works best with larger pellets that give a well defined
and consistent impact mark. "size" ignores features much larger than the typical pellet size. If a conventional pattern plate target with a bulls-eye and pre-marked segments is scanned-in, the "size" setting can suppress these features of the target. |
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Manually add or delete single pellets. Clicking will add a 'manual'
pellet - shown as a blue marker. SHIFT+clicking over a manually generated
pellet mark will delete it. SHIFT+click over an automatically generated
pellet mark will exclude the pellet from the analysis. (see Manual
Pellet and Deleted Pellet
graphics) |
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Horizontal / Vertical fields to enter the true distance indicated
by the scale setting arrows. |
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Update the analysis panel with the latest status of the image. |
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The distances may be input in imperial inches or metric cm.
However, all outputs are displayed in inches and graphical output is
shown with respect to a 30" and 20" circle. |
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Open a camera image of a shot pattern.
Note that the image must be in JPEG format and at least 200 x 200 pixels
in size. The higher the contrast of the pellet marks against the background,
the better the automatic pellet recognition will work. Remember the
old computer adage of "Rubbish in, rubbish out!" |
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Open a previously saved analysis
file. Note that only the Analysis Panel and Graphic will be reloaded
to allow viewing of the Analysis Graphic or editing of the Header Panel.
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Open a new window to allow multiple
saved Analysis Files to be averaged. (see
Averaging Data.) |
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Open a previously saved 'Average
File'. (see
Averaging Data.) |
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Closes all open windows and then
quits the programme. Note that any windows that have been 'minimised'
will remain open and the programme will not quit. These windows must
be expanded and "Quit and close all" called again or each window should be
closed individually. |
"POA x/y" are the 'Point of Aim' of the mean of the pellets compared with the point of aim indicator as positioned on the original image. x= horizontal placement, y= vertical.
"spread x/y" are the distances from the centre of the spread that would account for 68% of the shot (the "1-sigma" value) if the distribution was a perfect normal.
"75% shot diameter" should be read as the diameter inside which on average approximately 75% of the shot would fall. It is a convenient way of expressing the width and height in a single number that has some practical significance. (For the statistically inclined it assumes that the x and y spreads are uncorrelated. In practice this is not unreasonable since if the correlation is pronounced that is the bigger problem, not the accuracy of this radius estimate!)
"corr
/ sig" are the Correlation and Significance respectively. The correlation
(rs) is based on the Spearman Rank Correlation algorithm. If these
terms are not familiar it is suggested that they are either ignored
(recommended!) or the guidance of a statistics book is sought. However,
in simple terms, the correlation relates to how closely tied the 'y'
vertical position is to the 'x' horizontal. For example, the diagram below
shows a correlation close to 1. That is, there is a high degree of correlation
between the x and y position of the pellets. A correlation of -1 would
be a an equally pronounced correlation but sloping downwards. Ideally, the
shotgun pellets will have a correlation of zero. The correlation analysis is included
for completeness. Referring again to the picture below, the distributions
in the vertical and horizontal would be shown by the simple graphics in the Analysis
Panel/Graphic as being quite good: similar vertical and horizontal; no gaps in
the centre; symmetric about the centre. However, clearly something is wrong! The
correlation figure would show this. In practice any correlation will be less
obvious to the eye, but the figures should reveal if there is any systematic
error.
The statistical significance
(i.e. the confidence one has that the result is real and not the result
of chance) of the correlation is given by: t = rs * sqrt( (N-2)
/ (1 - rs * rs) ). For a large number of pellets ( > ~100) a significance
above approximately 4.0 indicates a high level of confidence that the
correlation rs is significant and not just a random event.
You are very, very unlikely to ever need this.
10" Dia., 10-20", 20-30". This is simply the number of pellets falling within the regions indicated. Please note that 10-20" and 20-30" are annuli! The number of pellets inside the 30" circle is the 10" Dia. value plus the 10-20" value plus the 20-30" value. If the number of pellets in the shell has been entered the percentages are also shown.
The 'total' is all pellets detected. This may include outliers that are not shown on the analysis panel graphic.
'Oberfell'. This is the number of non-overlapping 5" diameter discs that can be positioned in the 30" circle without falling on a pellet. Please note that the algorithm used under-reads if there are very few pellets within the circle. According to Oberfell p47, an empty 30" circle can accommodate 27 non-overlapping 5" discs. The algorithm as implemented records approximately 22. It was beyond this author to come-up with a fast algorithm for automatically replicating this result. However, for more realistic results the algorithm is reliable. This can be shown by manipulating pellets manually. It is also worth bearing in mind that the method of drawing in circles by hand is also non-perfect!
An edge-on clay is represented by a disc with the same area as an edge on standard sized UIT clay as used in the UK (25mm high x 110mm diameter - Laporte. 26mm high x 110mm diameter - CCI ). A "full-on" clay is represented by a disc of diameter 110mm (Laport, CCI data). By passing these discs across the pattern of pellets, the number of times the disc is 'hit' by at least one pellet versus the number of times it is completely free of pellets gives an estimate of the likelihood of the clay being hit.
The first three columns titled 10" Dia, 20" Dia and 30" Dia are simply estimates of the likelihood that the full-on or edge-on clay will be broken averaged over the given circle. This likelihood is estimated by passing the 'clay' across the target area and noting how many times the clay covers a pellet and how many times it does not.
Although this seems seductively simple, rating all areas of the 20" or 30" area equally may not be the best way to rate the pattern. What happens if there is a 'blown' pattern? That is one where a clay (or bird) could pass through the middle of the pattern without being hit even though there are plenty of pellets in the circle as a whole. Intuitively one can appreciate that the centre of the pattern is far more important than the fringe. If the shooter has done his part and centred the pattern on the target he should expect a kill. This is critical to trap and skeet shooters where top scores can approach 100%. The question is how to give the centre of the pattern greater importance when rating the pattern.
The columns titled 'Centre weighted sum' and 'Centre weighted norm' offer two alternatives.
The pattern is divided into the centre 10" diameter circle, an annulus 10"-20" diameter and an outer annulus 20"-30" diameter. Note, the relative areas of these regions are 1 : 3 : 5.
The 'Centre weighted sum' is simply the average of the hit probabilities of each of the three regions. Note that by using this regime, the centre 10" diameter disc is weighted at 1/3rd of the total compared with 1/9th using uniform weighting.
'Centre weighted norm' weights the centre
of the pattern even more heavily. The weighting is based on a Normal
distribution. The rationale for this is based on the premise that the
shooter will centre his shots about the target in much the same way as
a rifle or pistol shooter. Over a large number of shots the variation
about the target will probably follow a Normal or Gaussian distribution.
(See 'Background' for a brief explanation of
the Normal distribution.) Assume the shooter's variation is contained
within '3-sigma' of variation (~99.7%) and that this equals the 30" diameter
circle (sadly, better than me!). Using this regime the centre 10" diameter
disc is weighted 0.68, the middle annulus 0.27 and the outer 0.05. This
weights the hit probability with the same weighting as the probability of the
shooter's ability to place the shot, thus giving a truer estimate of the
practical likelihood of a hit. Clearly
this is open to debate. One could argue about how accurate the shooter
really is - should we assume instead that the 30" diameter circle is the
'2-sigma' level, that is ~5% of the time the shooter misses the 30" circle?
It is probably best to simply say there are a number of ways to justify
the relative weighting! However, as presented, the simple hit probability over a
30" circle would be applicable to a beginner or field shooter, the 'centre
weighted sum' method would be for an intermediate shooter and the 'normal
weighted distribution' for an expert.
Menu Functions of the Average Panel.
Interpreting the Average Panel Results.
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Add an earlier Analysis File to this
Average Panel. |
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Add an earlier Average File to this
Average Panel. |
Delete the file(s) highlighted
in the list of the Average Panel.
For a pistol or rifle shooter it is simple to establish what constitutes a 'good' cartridge and gun combination. It is simply the combination that gives the tightest group. Those who have experimented with different cartridges and in particular home loading will know what a wide range of results can be had from a single gun. The key concept to grasp is that what is sought is repeatability. With rifles and pistols one may get a 'tight' group with the occasional wild flier, or a consistent middling sized group, or best of all the consistently tight group. With a shotgun, all of these phenomena are probably happening, but difficult to 'see' given the hundreds of pellets.
One clear lesson that can be drawn from the rifle and pistol world is that one shot tells nothing! A number of shots must be made to show the average.
Given a number of test patterns, what constitutes a good shotgun and cartridge performance is still not clear. Using the rifle and pistol example, one should be trying to achieve consistent results. Consistent bias can be adjusted out. If the spread is a little wide, the choke can be adjusted in the same way as the rifle shooter can adjust the sights to correct for an off-centre group. However, if chokes are fixed, knowing the relative spread of various shells is in itself useful information. Consistency is measured by the variation of the pattern widths. For example, if a shell has a pattern with a reported spread of 8" (the 'E' field in the above figure), and every shell measured achieves this, it would be considered very repeatable (and almost impossible!), i.e. the spread on the 8" would be zero (reported in 'F' and 'G' fields).
The averages can be a little misleading. Think back again to the rifle and pistol scenario where the group was generally good, but there was one flier where clearly something 'one-off' had happened, perhaps a short charge of powder or bad crimp. The shotgun equivalent would be the 'blown' pattern. There is no easy way to analyse this by looking at averages with a shotgun. One must look at the probabilities of kills versus position in the pattern. If a miss is found in the centre of the pattern that is normally quite dense, then this would indicate a blown pattern. The analysis software allows the user to look at how reliably 'edge-on' or 'face-on' clays are hit. (A 'face-on' clay is also close to the 5" disc typically used to describe game.)
In summary, the analysis software
allows the user to look at each pattern in detail to confirm an even
spread (i.e. no 'fliers' or blown patterns) and then look at the average
results to compare the consistency and average spread of different shells.
A measure of consistency might be the "+/-" value of the spread horizontally
and vertically and if the gun is also shot from a rest, the variation
in the point of aim relative to the mean of the pattern.
How to deal with 'fliers' or outlier pellets is a difficult topic to resolve. In earlier versions of the software the advice given here was to ignore obvious 'fliers'. However, I'm now inclined to include all pellet marks. The reasons for this are:
Make sure that all pertinent information is marked on the target and captured by the digital camera. Notes can always be blocked from the analysis area. Make sure the reference distance is marked on the target for setting the image scale.
The Normal distribution features strongly in this analysis of shotgun patterns. The picture below illustrates its main features:
The graph shows the relative
probability of an 'event' happening versus its distance from the mean
(average) which in the picture above is shown as zero.
It will be seen that the likelihood of an event occurring is greatest
nearest the mean. The distance +/- "1-sigma" accounts for approximately
68% of events, the distance +/- 2-sigma for 95% of events and the +/-
3-sigma range accounts for 99.7% of all events. This type of distribution
model fits many naturally occurring observations, for example, heights
of people, test scores, examination marks etc. Oberfell and Thompson
also found that the average pattern distribution from a shotgun could be modelled by the Normal distribution. It is important to note that
the Normal distribution does not define the pellet distribution, it is
just a model that fits the observed distributions quite well. The closeness
of the distributions (shown by the histograms in the Average Results Panel
and Analysis Graphic) and the ideal Normal distribution should be convincing
enough that the Normal distribution is a useful tool for characterising
the distributions. (It is
a guess on my part that rifle, pistol and shotgun users will tend to aim
about the target with a variance that is also approximated by a Normal
distribution.)
The value 'sigma' is used to indicate the width of the distribution. The value of sigma can be used to compare one shell against another for a given choke to see which holds the tightest pattern and hence which will be able to carry a useful pattern the longest distance. Alternatively, skeet shooters may be interested in obtaining the widest spread possible.
To demonstrate that the shell
and gun combination work well together, the patterns should be as
repeatable as possible in much the same way as a rifle shooter looks
for minimum variation shot to shot. The big difference is that rather
than measuring a single distance (the maximum spread), the shotgunner's
measure of repeatability is how all the pellets behave together. One
way of doing this is to fit all the pellet positions to a model and then
look at how the parameters of the model vary. In this case the Normal
distribution is employed as the model.
A measure of repeatability of
the pattern is given by how sigma varies from shot to shot. Perhaps
surprisingly to the uninitiated, the distribution of the value of the
sigmas is itself a Normal! Thus we can have a 'sigma' value for the
variation of the sigma of the spread of the pellets distributions as
measured shot to shot!
The main source of reference (and part inspiration) for this work is a wonderful little book by the title of, "The Mysteries of Shotgun Patterns" written by George G. Oberfell and Charles E. Thompson, published by Oklahoma State University Press, 1957.
As well as many, many test targets, this book in turn cites work done by others in their efforts to deduce how shotguns perform.
One over-arching finding of Oberfell and Thompson (henceforth O&T) is that on average, over a large-number of shots, the pellet distribution follows that of a 'Normal' (also known as Gaussian) distribution.
The method of rating a shotgun developed by O&T is based on counting the gaps in a pattern. To ensure there is a reasonable probability of a gap, the test distance is 40 yards and No.6 shot recommended. As well as ensuring a reasonable likelihood of having gaps to measure, the number of pellets is low enough to be counted by hand. Based on the performance at 40 yards, performance at closer distances can be deduced.
With the availability of fast,
low-cost computers the analysis can be more sophisticated. Performance at
closer ranges can be confirmed and repeatability shot-to-shot can
be investigated. However, generating more data then presents the problem
of how to interpret the results. One of the great strengths of the Oberfell
& Thompson method is that it rates the shotgun in simple terms
- normal, poor, excellent etc.
The "Numerical Recipes" series
is a great source for algorithms across a whole range of science,
engineering and maths. The Spearman Rank-Order Correlation algorithm came from Numerical
Recipes in C. Authors: William H. Press, Brian P. Flannery, Saul A.
Teukolsky, William T. Vetterling. Cambridge University Press, ISBN 0-521-35465-X.
