Possible problems with Grain and Pattern counting

• No patterns detected Threshold is too high, mismatch weight is too negative, or match weight is too low; or, contrast is too low in image.
• Too many patterns detected Threshold is too low, mismatch weight is not negative enough, or match weight is too high. The optimum threshold is different for each type of image. The ideal threshold can be estimated visually by watching the numbers in the information box, and determining the signal at the point at which non-patterns begin to be detected. Interrupt the counting at this point and set the threshold to the value of the signal shown in the information box.
• Same pattern counted more than once; or, algorithm gets stuck on one pattern (coordinates don't change). This is a bug; please report it.
• Processing is too slow. Convert image to grayscale. This will increase speed at least 2.8 fold. Converting image to 8 bits will also help.
• Message box says ``0 Patterns found'', even though it found patterns on the same image earlier. You may have accidentally clicked on the background or menu bar, deselecting the image. Click on image and repeat.
• Message box says ``Neuron count mismatch''. This message occurs when you click on a different image while the algorithm is counting. The buffers are incorrect for the new image, so the algorithm aborts.
• Small red box indicating location of pattern is off-center. This occurs when defining the pattern, if the region selected for the pattern is not centered on the pattern (i.e., too much background is included in the pattern on one side).
• Large areas with shading similar to the pattern are identified as numerous instances of the pattern. This is caused by selecting an insufficient amount of background around the prototype pattern; or the mismatch weight is too low.

Examples

Size distribution using quick segmentation

Here is an example of an astronomical image after analysis by the quick segmentation algorithm. The threshold was set to 0.8 so that only the larger stars are counted. Each star that was counted is automatically labeled with its relative size. The size of a given object depends on the threshold and will be larger if the threshold is smaller, because more pixels are present in the distance matrix which is used to find grains. The grain counting dialog box is shown at right.

$\parbox{4in}{ \baselineskip 11pt The size distribution graph (not ... ...d verify that the results obtained are consistent with their expectations. }$