Texture Feature Extraction Method Based on Improved WLD
Guo Xianca · Jisuanji gongcheng · 2015
Aiming at the shortage of the discriminative ability to texture patterns for image texture classification using Weber Local Descriptor( WLD),an improved WLD based on Positive and Negative Gradient Features( WLD-PNG) is proposed. Positive and negative gradients are characterized by computing positive and negative differential excitations for preserving signed grayscale change information,and local texture structure information is represented by uniform Local Binary Patterns( u LBP). Combine both of them to build the image texture feature. The comparing experiments on the Brodatz and KTH-TIPS2-a texture databases demonstrate that WLD-PNG improves the distinctiveness of texture patterns,and has better robustness and low er computational complexity compared w ith original WLD,u LBP,WLD + u LBP and other improved WLD methods,etc.