Objective To study the application of color space clustering in handwritten text extraction. Methods The comparative effectiveness analysis of handwritten text clustering was implemented in Lab, LUV, YCbCr and the YIQ color space,respectively. Combining the spatial filtering enhancement and edge detection technique, the handwritten text information needed was extracted. Results In this paper, the selection of research object in Lab color space showed a better result of handwritten text extraction, which was conducive to the subsequent text recognition. Conclusion Dose color space clustering can not only avoid misjudge caused by loss of color information resulted from gray-scale transformation, but also achieve more accurate segmentation of color images while preserving the fast and simple advantages of the original threshold segmentation algorithm.