Binary pattern family is considered as a powerful tool for visual texture classification. Most popular methods improve the classification performance by multi-feature fusion. However, many sub-features are redundant and low-discriminative and the classification system has high computational complexity and unsatisfactory results. To handle above problems, this paper proposes a compact multi-pattern encoding descriptor for visual texture classification. First, we develop local extremum patterns and local center pattern to represent the neighborhood intensity changes. Then, we design a compact encoding scheme to encode local maximum, minimum and center patterns into a three-bit binary code, named MMC pattern. Finally, a compact multi-pattern encoding descriptor is proposed by combining the traditional local sign pattern and MMC pattern. Experimental results on five representative texture databases demonstrate that our method achieves the state-of-the-art texture classification performance.

二进制模式家族被认为是用于视觉纹理分类的强大工具。最流行的方法是通过多特征融合来提高分类性能。但是，许多子功能是多余的，低歧视性的，分类系统具有很高的计算复杂度和不令人满意的结果。为了解决上述问题，本文提出了一种用于视觉纹理分类的紧凑型多模式编码描述符。首先，我们开发局部极值模式和局部中心模式来表示邻域强度变化。然后，我们设计一种紧凑的编码方案，将局部的最大，最小和中心模式编码为三位二进制代码，称为MMC模式。最后，结合传统的局部符号模式和MMC模式，提出了一种紧凑的多模式编码描述符。