Abstract: Support Vector Machine（SVM） is a new method of pattern recognition，which has good generalization ability and outreach capacity.Automatic wood surface defects identification based on texture and support vector machine is studied.LBP texture feature extractor technology to complement down-dimensional processing of the wood image data is adopted，and the distribution traits of different wood surface defects is studied.With support vector machine classification algorithm，implementes fast and accurate automatic identification to judge whether the wood surface had any defects or not.And in locating the exact position of defects automatically is achieved.Many cross validation experiments indicted that support vector machine classification algorithm had strong recognition abilities to wood surface defects and the identification rates reached up to 96% upwards.