DESIGN OF A DUAL-CAMERA SYSTEM FOR POULTRY CARCASSES INSPECTION

Abstract

Two dual-camera systems were developed for on-line inspection of poultry carcasses: one to image the frontof the bird and the other to image the back. Each system consists of two identical black and white cameras equipped withinterference filters of 540 nm and 700 nm. Both cameras capture spectral images simultaneously. Object-oriented analysiswas performed to identify the attributes of individual software components and the relationships among these softwarecomponents. These individual software components were then organized by the object patterns to form a softwarearchitectural framework for on-line image capture, off-line development of classification models, and on-lineclassification of carcasses into wholesome and unwholesome categories. Model development and testing was performedon 331 chickens independently classified by a veterinarian. For off-line model development, the accuracies fordifferentiating between wholesome and unwholesome carcasses were 96.2% and 88.5% at 540 nm and 700 nm,respectively, for the front images and 95.7% and 85.1% at 540 nm and 700 nm, respectively, for the back images. On-lineclassification for 128 new samples combined the filter information within each system, using selected neural networkmodels. The front imaging system gave accuracies of 91%, 98% and 95% for normal, abnormal and combined carcasses,respectively. The back imaging system gave 84%, 100% and 92%.