Hyperspectral and multispectral imaging techniques were used to detect chicken skin tumors. Hyperspectral images of eight tumorous chickens were taken in the spectral range of 420-850 nm. Principle component analysis was applied to select useful wavelength bands (465, 575, 705 nm) from the tumorous chicken images. A multispectral imaging system capable of simultaneously capturing three registered images was used to image 60 tumorous and 20 normal chickens. Multispectral image analysis was performed to generate ratioed images, which were then divided into regions of interest (ROT's) classified as either tumorous or normal by a veterinarian. Image features for each ROT (coefficient of variation, skewness and kurtosis) were extracted for use as inputs to fuzzy classifiers. The fuzzy classifiers were able to separate normal from tumorous skin with increasing accuracies as more features were used. In particular, use of all three features gave successful detection rates of 9 1 % and 86% for normal and tumorous tissue, respectively.

Date Published: 13 March 2001
PDF: 10 pages
Proc. SPIE 4206, Photonic Detection and Intervention Technologies for Safe Food, (13 March 2001); doi: 10.1117/12.418732

Published in SPIE Proceedings Vol. 4206:
Photonic Detection and Intervention Technologies for Safe Food
Yud-Ren Chen; Shu-I Tu, Editor(s)