This paper presents an approach to texture segmentation by thresholding based on compactness measures of fuzzy sets to determine thresholds of an ill-defined image. The extension of fuzziness in the texture feature space provides more meaningful results than by considering fuzziness in gray scale domain. The effectiveness of the algorithm is demonstrated by comparison with other traditional non-fuzzy methods or the controversial fuzzy method in gray scale alone. In addition, the efficiency of our algorithm is further improved by parallel implementation using distributed shared memory workstations.