Detection of textural defects using a one class support vector machine

Method for detecting textural defects in an image. The image, which may have an irregular visual texture, may be received. The image may be decomposed into a plurality of subbands. The image may be portioned into a plurality of partitions. A plurality of grey-level co-occurrence matrices (GLCMs) may be determined for each partition. A plurality of second-order statistical attributes may be extracted for each GLCM. A feature vector may be constructed for each partition, where the feature vector includes the second order statistical attributes for each GLCM for the partition. Each partition may be classified based on the feature vector for the respective partition. Classification of the partitions may utilize a one-class support vector machine, and may determine if a defect is present in the image.Board of Regents, University of Texas Syste