Construction of rotationally invariant 2D wavelets is important in image processing, but is difficult. In this paper, the discrete form of a 2D rotationally invariant wavelet is constructed by back-projection from a 1D symmetrical wavelet. Such rotationally invariant 2D wavelets allow effective edge detection in any direction. These wavelets are combined with the 2D directional wavelets for the use in non-maximum suppression edge detection. The resulting binary edges are characterized by finer contours, differential detection characteristics and noise robustness compared to other edge detectors in various test images. In particular, where fine binary edges in noisy images are required, this novel approach compares favorably to the classical methods of Canny and Mallat with detection of more edges thanks to the implicit denoising properties and the full rotational invariance of the method.
Abstract. BACKGROUND: Doctors who practice Traditional Chinese Medicine (TCM) diagnose using four methods -inspection, auscultation and olfaction, interrogation, and pulse feeling/palpation. The shape and shape changes of the moon marks on the nails are an important indication when judging the patient's health. There are a series of classical and experimental theories about moon marks in TCM, which does not have support from statistical data. OBJECTIVE: To verify some experiential theories on moon mark in TCM by automatic data-processing equipment. METHODS: This paper proposes the equipment that utilizes image processing technology to collect moon mark data of different target groups conveniently and quickly, building a database that combines this information with that gathered from the health and mental status questionnaire in each test. RESULTS: This equipment has a simple design, a low cost, and an optimized algorithm. The practice has been proven to quickly complete automatic acquisition and preservation of key data about moon marks. CONCLUSION: In the future, some conclusions will likely be obtained from these data; some changes of moon marks related to a special pathological change will be established with statistical methods.
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