Abstract: In the process of bamboo product processing, it mainly relies on human eyes to recognize and classify the color of bamboo strips, which leads to problems such as high labor intensity, low efficiency, and large errors. In this regard, a bamboo sliver color difference classification and detection system through Matlab image processing technology was designed. Firstly, the standard bamboo strips and sample bamboo strips were transformed into color space, after which the bamboo strips were preprocessed by median filtering and different color components were extracted. Then, the color characteristic data of bamboo sliver image was extracted from HSV color space, and the color intersecting histogram of each component of bamboo sliver in HSV color space was obtained, and the corresponding similarity value was calculated. By comparing the similarity value of bamboo strips, the color aberration classification was carried out and the relationship between the bamboo strips and the color aberration grade was established. Finally, the color difference classification test of the processed bamboo strip image was carried out. The experimental results showed that the classification and detection accuracy of color space histogram intersection method was up to 92.22%, and the algorithm running time was 536 ms. Compared with the angle cosine similarity method, the average recognition accuracy was increased by 4.44%, while the average running time was decreased by 63.44%.