Automatic discrimination of features in grey‐scale images

SUMMARY Automatic setting of discriminator thresholds to select features from grey‐scale images is desirable to reduce variations due to operator variability, and to adapt to changing illumination or sample characteristics. This can be carried out in several ways. One locates minima in the original brightness histogram. For images in which minima are absent or poorly defined other techniques are preferred. Settings that minimize the change in total feature area or perimeter with changes in the threshold setting are suitable for a wide variety of images. After processing to extract edges a fixed percentage of the number of pixels in the image may be useful.