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As one of the most important part of the Concentrated Photovoltaic (CPV) system, the tracking accuracy and sensitivity of the solar tracker has a significant influence on the lighting rate and power generation rate of CPV system. The CPV solar tracker based on ARM tracks the sun mainly by using the CMOS sensor. In order to improve the tracking sensitivity, a method of sun spot center orientation based...
This paper proposes a real-time traffic sign detection system. In order to extract accurately the shape feature of the traffic sign, reduce the computational load and further improve the traffic sign detection rate, a novel approach based on surround suppression of texture edges and cascade detector is presented. The principle of surround suppression mainly adds a computational step to the canny edge...
Many of the recently popular shape based category recognition methods require stable, connected and labeled edges as input. This paper introduces a novel method to find the most stable region boundaries in grayscale images for this purpose. In contrast to common edge detection algorithms as Canny, which only analyze local discontinuities in image brightness, our method integrates mid-level information...
The incidence of melanoma rises rapidly in Caucasians after the age of 20, and US statistics show about 1 million new cases every year. Specialists in the field are highly accurate in determining whether a skin lesion is cancerous or not based solely on a visual inspection. No systems exist for accurately classifying skin spots. The first stage in the development of such a system is to identify the...
A comparison study of well known edge detection methods (Sobel, Prewitt, Canny, LoG, Zerocross, Roberts) for binary images revealed that these methods have a tendency to distort images, especially under noisy conditions, with some methods exhibiting image distortion even under noiseless conditions. While Sobel, Prewitt, and Canny performed better overall, it was observed that they do not completely...
We propose an edge detector based on the selection of well contrasted pieces of level lines, following the proposal of Desolneux-Moisan-Morel (DMM) [1]. The DMM edge detector has the problem of over-representation, that is, every edge is detected several times in slightly different positions. In this paper we propose two modifications of the original DMM edge detector in order to solve this problem...
Edges are basic low level primitives for image processing. Edge detection is one of the most common operations in image analysis. In this paper a new implementation for edge detection methods using LVQ neural network is proposed. For instance Susan and Canny and Sobel edge detectors are modeled by neural network and simulation results are very promising.
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