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In advanced IC manufacturing, as the gap increases between lithography optical wavelength and feature size, it becomes challenging to detect problematic layout patterns called lithography hotspot. In this paper, we propose a novel fuzzy matching model which extracts appropriate feature vectors of hotspot and nonhotspot patterns. Our model can dynamically tune appropriate fuzzy regions around known...
Ultrasound imaging has been widely used to investigate the morphological changes during skeletal muscle contraction. In this study, the ultrasound images were recorded from extensor muscle during finger flexion, and the optical flow algorithm was used to recognize the muscle deformation for different fingers' flexions. The preliminary results demonstrated that the directions of optical flow and deformation...
Wood species recognition is a texture classification problem that has yet to be well studied. The textures observed on the cross section surface of the wood samples can be used to identify the species of the wood. In this paper, we tested various texture classification techniques, i.e. grey level co-occurrence matrices (GLCM), Gabor filters, combined GLCM and Gabor filters as well as covariance matrix...
An automated wood species recognition system using computer vision techniques is not widely used today, it is highly needed in various industries, but a wood identification expert is not easily trained to meet the market demand. This paper proposes a rotational invariant method using the grey level co-occurrence matrices (GLCM) as the features, an energy value representing the similarity between the...
The grey-level co-occurrence matrices (GLCM) has been widely used for various texture analysis implementations and has provided satisfying results. The conventional GLCM method is two dimensional as it focus on the co-occurrence of the specific pixel pairs. The one-dimensional GLCM reduces the matrices to a single dimension by focusing only on the differences of the grey level between pixel pairs...
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