Microstructure analysis of silk samples using mueller matrix determination and sparse representation

In this paper, we propose to use Mueller matrix determination and sparse representation to classify silk samples washed in different detergents. Different detergents have different effects on the same silk samples after washing, and we distinguish their diversities in the Mueller matrix images(MMI) instead of visible light images(VLI). Compared with VLI, Mueller matrix, also known as polarization image, reflects the wavelength-scale microstructure and some optical properties of samples, and focuses on extracting the index to research the polarization property. To achieve a good performance with the microstructure analysis, we utilize the method of sparse representation which uses the reconstruction error for classification. Generally speaking, we introduce to combine Mueller matrix with sparse representation in the classification of the same silk samples washed in different detergents, and the high precision in experimental results indicates that our method works well.