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)
SUMMARY In camera-based object recognition and classification , surface color is one of the most important characteristics. However, apparent object color may differ significantly according to the illumination and surface conditions. Such a variation can be an obstacle in utilizing color features. Geusebroek et al.'s color invariants can be a powerful tool(More)
Image relevance evaluation in conventional Dictionary (Database) Relevance evaluation Input (Query) Content-Based Image Retrieval (CBIR) researches typically A 1. Image partition 4 relied on a given criterion. However, it is important that this Featureextractionen criterion can be changed according to the use of the image matching database. This work(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 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 [1] to make it scale invariant and enhances its(More)