To address the problems of human-computer interaction, poor separation, low efficiency, and difficulty in seed selection in the traditional image foreground-background separation algorithms, we propose an automatic image-foreground-background separation algorithm based on the texture features extracted in the Lab color space. First, we segment the image into blocks and convert it into a CIE-Lab color space established by the international commission on illumination (CIE). Then, we extract the color and texture features of each image block and select seeds. Finally, we use a region growing algorithm for image separation and region merging to reduce over separation. The experimental results show that the proposed algorithm is superior to the traditional algorithm in terms of the separation results, processing time, and algorithmic complexity.