Abstract: Method and apparatus for the detection of faults in industrial objects and signalling such faults to handling apparatuses. According to the invention, the image is taken of a sample object by a television camera or other sensing device; the image is digitized and stored in a frame memory. The digitized sample (standard) image is then divided into small areas, for each of which the square root of variance (standard deviation) for the luminance levels of dots belonging to each area is calculated and stored. The same operations and elaborations are followed for each object to be checked and the obtained values are compared with those of the sample. When the differences thereof are above predetermined thresholds, an output signal is generated for distinguishing the fault and generally the faulty object and for controlling a handling apparatus for the objects.

Abstract: Method and apparatus for real time recognition of test images by comparison with sample images. The test image to be recognized is scanned to produce a plurality of analog signals of the luminance levels. These luminance signals are screened to eliminate background signals and are converted to digital signals. A distribution function of the occurrence frequency versus the luminance level is determined from the test image signals. Typical parameters of said distribution function are calculated and compared with sets of stored corresponding parameters derived in a similar manner from known reference sample images. A recognition signal is outputted to indicate the sample image which most closely resembles the test image as determined by said comparison, provided that the quantitatively determined differences between test and sample images are below a predetermined threshold value.