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ABSTRACT AN algorithm for processing grey level images from a line scan camera of near-infrared reflectance from an apple surface for bruised tissue detection is presented. The image data is filtered to remove interference due to pixel-to-pixel variations in the camera and background noise and is thresholded to separate possible bruise tissue from the rest of the apple tissue in the image. Clusters of black pixels (grey level = 0) in the resulting binary image that are representative of potential bruises are analyzed to determine their size and shape. If the shape of the cluster is nearly circular, it is determined to be a bruise. From this information, the amount of bruise area on the fuit may be determined, and the fruit graded. Grey level images of other defects including scab, bird pecks, russeting, hail damage and cuts were examined. Scab, bird pecks and hail damage could be discriminated in the line scan image by the lower grey level of these areas in the unprocessed image..