Abstract
Existing vision-based automatic inspection systems are mainly devoted to mechanic and electronic applications, their introduction into other fields being strongly limited by the need for operating in non-controlled environments and by the lack of an accurate definition of the inspection task. In this paper, an intelligent vision system aimed at the detection of defects on chicken meat before packing is presented. The detection of defects relies on the analysis of the chromatic content of chicken images. Possibly defective areas are first extracted by means of morphological image reconstruction, and then classified according to a predefined list of defects. Experimental results show the effectiveness of the proposed approach, thus proving the feasibility of automatic inspection of alimentary products.
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