عنوان المقالة: Optimization of discrete wavelet transform features using artificial bee colony algorithm for texture image classification Optimization of discrete wavelet transform features using artificial bee colony algorithm for texture image classification
Fthi M. Albkosh, Muhammad Suzuri Hitam, Wan Nural Jawahir Hj Wan Yussof, Abdul Aziz K. Abdul Hamid, Rozniza Ali
المؤلفون بالإنجليزي
Fthi M. Albkosh, Muhammad Suzuri Hitam, Wan Nural Jawahir Hj Wan Yussof, Abdul Aziz K. Abdul Hamid, Rozniza Ali
الملخص الانجليزي
Selection of appropriate image texture properties is one of the major issues in texture classification. This paper presents an optimization technique for automatic selection of multi-scale discrete wavelet transform features using artificial bee colony algorithm for robust texture classification performance. In this paper, an artificial bee colony algorithm has been used to find the best combination of wavelet filters with the correct number of decomposition level in the discrete wavelet transform. The multi-layered perceptron neural network is employed as an image texture classifier. The proposed method tested on a high-resolution database of UMD texture. The texture classification results show that the proposed method could provide an automated approach for finding the best input parameters combination setting for discrete wavelet transform features that lead to the best classification accuracy performance.
تاريخ النشر
06/12/2019
الناشر
International Journal of Electrical and Computer Engineering (IJECE)
فتحي مفتاح عبدالرزاق البكوش | FTHI M A ALBKOSH | 346