Performance evaluation of wavelet scattering network in image texture classification in various color spaces
This work provides a comparative analysis for researchers in image analysis, offering a recommendation for color space selection in texture classification tasks, but it is incremental as it applies an existing method to new data.
The paper evaluated the performance of wavelet scattering networks for color texture classification across different color spaces, finding that opponent RGB-based networks outperformed others on the KTH_TIPS_COL database.
Texture plays an important role in many image analysis applications. In this paper, we give a performance evaluation of color texture classification by performing wavelet scattering network in various color spaces. Experimental results on the KTH_TIPS_COL database show that opponent RGB based wavelet scattering network outperforms other color spaces. Therefore, when dealing with the problem of color texture classification, opponent RGB based wavelet scattering network is recommended.