Identification of cow/sheep leather based on the distribution features of leather pores
The performance and value of leather vary with its type,it is necessary to develop leather identification methods.Most current methods for identifying leather types require complex equipment or rely on the experience of testers.Image algorithms are used to process microscopic images of leathers and analyze the location of pores.Based on the differences in pore distribution between cow leather and sheep leather,two features are extracted to characterize the differences between them.Linear classifiers are used to train the feature data of images.The trained model could distinguish between cow leather and sheep leather with an ac-curacy rate of 89.2％.The method in this paper only requires an optical microscope.The identification process fully utilizes image processing algorithms and data analysis,independent of subjective factors.
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