Since traditional shadow detection methods based on paired-regions are prone to over-segmentation in complex texture regions, they always have high computational complexity which affects the detection result to a certain extent. Therefore, an improved shadow detection algorithm is presented, using clustering method to merge divided areas and decrease over-segmentation. Besides, support vector machine (SVM) is established to classify the features of paired regions, so both algorithm efficiency and shadow detection effect are improved. Simulation results indicate that the running time of the proposed algorithm is remarkably reduced compared with the traditional one. Moreover, the shadow detection effect is more accurate than that of the original method for complicated texture images.