Biological tissue identification using a multispectral imaging system

A multispectral imaging system enabling biological tissue identifying and differentiation is presented. The measurement of beta(lambda) spectral radiance factor cube for four tissue types (beef muscle, pork muscle, turkey muscle and beef liver) present in the same scene was carried out. Three methods for tissue identification are proposed and their relevance evaluated. The first method correlates the scene spectral radiance factor with tissue database characteristics. This method gives detection rates ranging from 63.5 % to 85 %. The second method correlates the scene spectral radiance factor derivatives with a database of tissue beta(lambda) derivatives. This method is more efficient than the first one because it gives detection rates ranging from 79 % to 89 % with over-detection rates smaller than 0.2 %. The third method uses the biological tissue spectral signature. It enhances contrast in order to afford tissue differentiation and identification.