Zhi-Heng Wang

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In this paper, we present a fast randomized circle detection algorithm applied to determine the centers and radii of circular components. Firstly, the gradient of each pixel in the image is computed using Gaussian template. Then, the edge map of the image, obtained by applying canny edge detector, is tackled to acquire the curves consisting of 8-adjacency(More)
We present a non-HT circle detection algorithm applied to search the centers and radii of circular or partially circular components present in the image. The line coincident with the gradient vector of each edge point and passing through the corresponding edge point is defined first. Then, for every pixel in the image, the number of the lines passing(More)
This paper presents a method for the detection of arbitrary triangle based on the property that the distance of the incenter to the edges of the triangle is equidistant and equal to the radius of the inscribed circle. The method is constructed by the following steps. Firstly, the orientation line of each edge point is computed from the edge-only image.(More)
In the present paper, a local mean-based K-nearest centroid neighbor (LMKNCN) technique is used for the classification of stars, galaxies and quasars (QSOS). The main idea of LMKNCN is that it depends on the principle of the nearest centroid neighborhood(NCN), and selects K centroid neighbors of each class as training samples and then classifies a query(More)
Pathological brain detection is an automated computer-aided diagnosis for brain images. This study provides a novel method to achieve this goal.We first used synthetic minority oversampling to balance the dataset. Then, our system was based on three components: wavelet packet Tsallis entropy, extreme learning machine, and Jaya algorithm. The 10 repetitions(More)
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