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In this paper, an image enhancement algorithm is presented for identification of corrosion areas and dealing with low contrast present in shadow areas of an image. This algorithm uses histogram equalization processing under the hue-saturation-intensity model. First of all, an etched image is transformed from red-green-blue color space to hue-saturation-intensity color space, and only the luminance component is enhanced. Then, part of the enhanced image is combined with the original tone component, followed by saturation and conversion to red-green-blue color space to obtain the enhanced corrosion image. Experimental results show that the proposed method significantly improves overall brightness, increases contrast details in shadow areas, and strengthens identification of corrosion areas in the image.

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This paper proposes an eye control system employing eye gaze tracking techniques that might be helpful for those limb disabled people with healthy eyes. Eye gaze tracking technique is attracting more and more research interest in recent years. With an aim to overcome the shortcomings of existing methods (e.g., high hardware complexity and low detection accuracy), we use the pupil-corneal reflection technique to develop an ameliorated Hough transform algorithm, which is the core unit of the proposed system. We also design a typing function as well as an efficiently blink detection function. With these functions, users can input numbers into the computer with their eyes only through a specifically designed head mount eye control device. Experimental results demonstrate that the proposed ameliorated Hough transform algorithm provides a satisfactory typing accuracy of 87%, much higher than its counterpart in the literature.