Keisuke Kameyama

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In this paper, we propose a relaxation-labeling algorithm for real-time contour-based image similarity retrieval that treats the matching between two images as a consistent labeling problem. To satisfy real-time response, our algorithm works by reducing the size of the labeling problem, thus decreasing the processing required. This is accomplished by adding(More)
In the experiments, the parameters that affect the similarity evaluation in a binary shape matching CBIR system were tuned to improve the retrieval ranking score. After tuning the parameters by PSO, it was found that the ranking of the retrieved images were improved according to the given criterion.
An automatic defect classification (ADC) system for visual inspection of semiconductor wafers, using a neural network classifier is introduced. The proposed Hyperellipsoid Clustering Network (HCN) employing a Radial Basis Function (RBF) in the hidden layer, is trained with additional penalty conditions for recognizing unfamiliar inputs as originating from(More)
We introduce an adaptation framework based on scale space filtering for making thinning algorithms robust against noise in sketch images. The framework takes a sketch image as input, produces a set of Gaussian blurred images of the input sketch and uses a thinning algorithm to produce thinned versions of the blurred images. The algorithm's output is then(More)
We introduce a statistical shape descriptor for Sketch-Based Image Retrieval. The proposed descriptor combines feature information in near and far support regions defined for each sketch point. Two feature values are extracted from each point, corresponding to near and far support regions from the point's perspective, and used to populate a 2-D histogram(More)
We review available methods for Sketch-Based Image Retrieval (SBIR) and we discuss their limitations. Then, we present two SBIR algorithms: The first algorithm extracts shape features by using support regions calculated for each sketch point, and the second algorithm adapts the Shape Context descriptor to make it scale invariant and enhances its performance(More)
Keywords: Thinning algorithm Robustness against noise Scale space filtering Sketch image preprocessing a b s t r a c t We apply scale space filtering to thinning of binary sketch images by introducing a framework for making thinning algorithms robust against noise. Our framework derives multiple representations of an input image within multiple scales of(More)