Title :
Recognition of Agricultural Objects by Shape
Author :
Schatzki, T. F. ; Grossman, A. ; Young, R.
Author_Institution :
Agricultural Research Service, Western Regional Research Center, Berkeley, CA 94710.
Abstract :
It is desired to enhance the outline of agricultural contraband in X-ray images of passenger luggage. Agricultural contraband consists of fruit, meats, animals, and plants. We suggest most contraband can be distinguished from other material by an elliptic, rather than rectangular, cross section. An algorithm is proposed to recognize such cross section using the erosion of the absolute gradient of the image. Only local convolution calculations are required. This algorithm is tested on a number of computed images as well as on X-ray images of model objects, isolated contraband, and contraband contained and obscured in baggage. The effect of image noise, object size, orientation, and obscuration is tested. It is shown that the proposed algorithm successfully enhances the outlines of desired items as small as 1-2 cm (7-11 pixels) to the exclusion of remaining material under the conditions expected in actual use.
Keywords :
Animals; Calculus; Image analysis; Image recognition; Plants (biology); Shape; Testing; X-ray detection; X-ray detectors; X-ray imaging; Agricultural contraband; X-ray imaging; contraband detection; enhancement; erosion; gradient; image analysis by desktop computer; image noise; object orientation; object size;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.1983.4767455