Analysis of hyperspectral fluorescence images for poultry skin tumor inspection

Seong G. Kong, Yud-Ren Chen, Intaek Kim, Moon S. Kim
2004 Applied Optics  
This paper presents a hyperspectral fluorescence imaging system with a fuzzy inference scheme for detecting skin tumors on poultry carcasses. Hyperspectral images reveal spatial and spectral information useful for finding pathological lesions or contaminants on agricultural products. Skin tumors are not obvious since the visual signature appears as shape distortion rather than a discoloration. Fluorescence imaging allows the visualization of poultry skin tumors more easily than reflectance. The
more » ... hyperspectral image samples obtained for this poultry tumor inspection contains 65 spectral bands of fluorescence in the visible region of the spectrum at wavelengths ranging from 425 nm to 711 nm. The large amount of 1 hyperspectral image data is compressed using a discrete wavelet transform in the spatial domain. Principal component analysis provides an effective compressed representation of the spectral signal of each pixel in the spectral domain. A small number of significant features are extracted from two major spectral peaks of relative fluorescence intensity that have been identified as meaningful spectral bands for detecting tumors. A fuzzy inference scheme, using a small number of fuzzy rules and Gaussian membership functions, successfully detects skin tumors on poultry carcasses. Spatial filtering techniques are used to significantly reduce false positives.
doi:10.1364/ao.43.000824 pmid:14960077 fatcat:qvw7j5j23fghlcovogeik65oge