Automatic Recognition Method for Optical Measuring Instruments Based on Machine Vision

• Published in: Transactions of Tianjin University Vol. 14; no. 3; pp. 202 - 207
• Main Author: 宋乐 林玉池 郝立果
• Format: Journal Article
• Language: English
• Published: Heidelberg Tianjin University 01.06.2008; State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China
• Subjects: Engineering; Humanities and Social Sciences; Mechanical Engineering; multidisciplinary; Science; 光学测量工具; 机器视觉; 神经网络; 自动识别; template matching; optical measuring instruments; neural network; automatic recognition
• DOI: 10.1007/s12209-008-0037-3
• ISSN: 1006-4982

Based on a comprehensive study of various algorithms, the automatic recognition of traditional ocular optical measuring instruments is realized. Taking a universal tools microscope（UTM） lens view image as an example, a 2-layer automatic recognition model for data reading is established after adopting a series of pre-processing algorithms. This model is an optimal combination of the correlation-based template matching method and a concurrent back propagation（BP） neural network. Multiple complementary feature extraction is used in generating the eigenvectors of the concurrent network. In order to improve fault-tolerance capacity, rotation invariant features based on Zernike moments are extracted from digit characters and a 4-dimensional group of the outline features is also obtained. Moreover, the operating time and reading accuracy can be adjusted dynamically by setting the threshold value. The experimental result indicates that the newly developed algorithm has optimal recognition precision and working speed. The average reading ratio can achieve 97.23%. The recognition method can automatically obtain the results of optical measuring instruments rapidly and stably without modifying their original structure, which meets the application requirements.