Abstract
Diffuse reflection of laser radiation by a biological tissue always gives rise to the formation of a biospeckle pattern. The biospeckle pattern depends on the surface irregularities and carries significant information about the surface roughness. Biospeckle imaging has been extensively applied to medicine, biology and agriculture for evaluating different types of biological tissues, since it is safe, simple and non-destructive optical method. In consequence of the texture properties of biospeckle pattern, various texture analysis methods have been presented in literature for extracting the information involved in biospeckle patterns. In this work, first, an experimental setup to simultaneously capture multiple biospeckle patterns from many cross-section areas of bovine articular cartilage tissue surface is investigated. Next, a new model based on local contrast measurement is proposed on the captured biospeckle patterns for final and proper estimation of the average roughness of the various cross-section areas of articular cartilage surface. The proposed model computes the local contrast for pairs of pixels at different neighborhood separation distances in order to obtain three contrast features. The obtained results showed that the contrast features can efficiently differentiate between the average roughness of the different cross-section areas of articular cartilage surface with 0.02 μm accuracy.