基于提升小波变换的指针式仪表图像边缘检测

为解决工业中对指针式仪表的自动检定,针对自动检定系统中所涉及的图像边缘检测技术难点,分析了现有传统算法的不足之处,提出一种有效的基于提升小波变换的边缘检测算法。该算法利用提升小波变换尺度的低通作用,避免受高频噪声影响,在传统边缘检测算法的基础上,提取低频轮廓。利用小波系数的方向性,结合方向性边缘检测算子,获得高频边缘信息,最后利用小波重构获得准确清晰的图像边缘,为后续Hough变换准确的提取指针提供了有利保障。实验结果表明,该算法得到的图像边缘较传统Canny算法更清晰准确,无虚假边缘,应用于仪表自动检测系统中是可行的。

Edge Detection of Analog Instrument ImageBased on Lifting Wavelet Transform

In order to solve the technical difficulties of the image edge detection involved in the pointer instrument automatic detection system based on computer vision industry, analysis of the shortcomings of existing traditional algorithms, propose an effective edge detection algorithm based on lifting wavelet transform. At first the algorithm avoided being affected by high-frequency noise using low-pass effect of lifting wavelet transform scale, and extracted low-frequency contour based on the algorithm of traditional edge detection. Using the directional of wavelet coefficients, combined with directional edge detection operator, accessed high-frequency edge information, so get clear and precise edge of image, and provided a favorable security for the extraction of accurate pointer using the Hough transform. Experiments show that the algorithm image edge was detected by the algorithm is more clear and accurate than the traditional Canny algorithm, and there is no false edge, and applying the algorithm to automatic detection system is feasible.