Search Results - "Kasvand, T."

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  1. 1

    Polyhedra Recognition by Hypothesis Accumulation by Dhome, M., Kasvand, T.

    “…A new method is presented for the recognition of polyhedra in range data. The method is based on a hypothesis accumulation scheme which allows parallel…”
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    Journal Article
  2. 2

    Recognition of kidney glomerulus by dynamic programming matching method by Yamada, H., Merritt, C., Kasvand, T.

    “…Dynamic programming was applied to locate the glomeruli in microscopic images of kidney tissue section. The glomeruli were modeled by a polygon whose sides…”
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    Journal Article
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    The k1k2 space in range image analysis by Kasvand, T.

    “…Range finder images may be segmented by using a decision space H(k1, k2) where k1 represents the maximum local surface curvature and k2 the minimum surface…”
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    Conference Proceeding
  8. 8

    Extraction edges in 3D range images to subpixel accuracy by Kasvand, T.

    “…A mixture of image processing and analytic technique is used to detect facets, edges, and corners in 3D laser rangefinder images. The methods do not require…”
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    Conference Proceeding
  9. 9

    Total 8-connectivity on the square raster by Kasvand, T.

    “…In order to avoid logical inconsistencies on the regular square raster, the foreground and the background in a binary image have to be treated differently…”
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    Conference Proceeding
  10. 10

    Combined measures toward restoration of temporal information from offline handwritten text by Alohali, Y., Alanzi, A., Suen, C.Y., Kasvand, T., Cheriet, M.

    “…The research described in this paper intends to restore temporal information out of offline handwritten words. Such a system can be a backbone to a number of…”
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    Conference Proceeding
  11. 11

    A near-neighbor processor for line thinning by Del Sordo, M., Kasvand, T.

    “…Since thinning is essentially a pattern mask matching process, a near-neighbor hardware structure seems the most appropriate manner to accomplish this task in…”
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    Conference Proceeding
  12. 12

    Motion estimation based on point correspondence using neural network by Zhu, P.Y., Kasvand, T., Krzyzak, A.

    “…An algorithm for estimating motion parameters of a rigid body from range data is presented. The best correspondence between two three-dimensional point sets is…”
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    Conference Proceeding