In sports, players have to perform body movement in a specific manner in order to obtain desired training effect. Badminton is one of Malaysia’s most popular sport, but there is still lack of research on action analysis focusing on this sport. In this paper, a method to analyze badminton action from depth map sequences acquired by Microsoft Kinect sensor is proposed. A compact and view invariant representation of the joint movement, namely region of movement index is generated from the three-dimensional coordinates of the tracked joint. Then, the overall or frame-based performance variation between the expert and learner is computed by mapping using dynamic time warping algorithm.
Images of scanning electron microscope are usually in the monochrome mode. A simple and user-friendly approach is proposed to improve the mechanical contrast of the scanning electron microscope grey images. Also, most colourization techniques involve image segmentation or region tracking, which tend to degrade the image with fuzzy or complex region boundaries. A technique is proposed, which is a hybrid between the Canny edge detection technique and the optimization technique. Compared with existing methods, the new Canny optimization technique gives satisfactory results for scanning electron microscope images.
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