In the textile industry, different types of foreign fibers may be mixed in cotton, and the foreign fibers seriously affect the quality of cotton products. The step of image segmentation is of vital importance in the process of the foreign fibers identification, which is, in the same way, the foundation for cotton foreign fiber automated inspection. This paper presents a new approach for fast segmentation of foreign fiber images. This approach includes four main steps, i.e., image transformation, image block, image background extraction, image enhancement and segmentation. In the first step, we transform the captured color images into gray-scale images, and invert the color of the transformed images. In the second step, the proportion relationship between target image and background was analyzed, and then the whole foreign fibers image was divided into several blocks based on the analysis results. In the third step, the background of foreign fiber image was extracted by image corrosion and gray-level correction. In the final step, the histogram of the gray-scale image was analyzed, and a piecewise linear transform model was proposed to enhance the image blocks based on the analysis results, and then the image blocks were segmented by Otsu’s method. The experiment results indicate that the proposed method can segment the foreign fiber image directly and precisely, and the speed of image processing is much faster than that of the conventional methods.