Chicken Carcasses Using Hyperspectral Fluorescence Imaging

This article presents a method for detecting skin tumors on chicken carcasses using hyperspectral fluorescence imaging data, which provide fluorescence information in both spectral and spatial dimensions. Since these two kinds of information are complementary to each other, it is necessary to exploit them in a synergistic manner. Chicken carcasses are examined first using spectral information, and the results are used to determine candidate regions for skin tumors. Next, a spatial classifier selects the real tumor spots from the candidate regions. It was shown that the method detected chicken carcasses with tumors, but failed to detect some tumors that were smaller than 3 mm in diameter. This study uncovered meaningful spectral bands for detecting tumors using hyperspectral imaging data. A detection system based on this method can improve the detection rate, and processing time can also be reduced, because the detection procedure is simplified by using a limited number of features, which reduces computational complexity. The resultant detection rate, false positive rate, and missing rate of the proposed method are 76%, 28%, and 24%, respectively.