In response to the problem of low efficiency of manual verification of medicines, a method for recognizing tablet position with improved MobilenetV3-Small network structure is proposed. The acquired original images are converted to the LAB color space, and the L channel under the LAB color space is employed with canny edge segmentation, morphological processing, image filling and single pill image frame selection, so as to position a single pill; the network structure of the MobilenetV3-Small is improved by loading pre-trained weights, using the K-means clustering algorithm to optimize the input size, modifying the network layer according to the feature map, etc.; by combining with the positioning method of image processing and the recognition method of improved MobilenetV3-Small network, the rapid and accurate detection of tablets is realized. Finally, on the 523 single pill images processed, the Loss value of the pill recognition is 0.000035, which verified the effectiveness of the algorithm.