An intelligent perception system for food quality inspection using color analysis

Modern manufacturing systems call for full-rate automated inspection of produced samples. A vision-based intelligent perception system (IPS) is presented making automated inspection of chicken meat feasible. The IPS analyzes RGB images framing the chickens after the slaughtering and plucking process and detects defects such as burns, hematomas and blisters, along with other relevant features. The vision module, which is the core of the system, operates by first extracting the chicken body from the background, then it segments the body into its anatomic subparts. Defective areas are identified by means of morphological reconstruction. Finally, defects are classified by comparing their features against the defect description contained in a reference database