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    NTHUR > College of Electrical Engineering and Computer Science > Department of Computer Science > CS Journal / Magazine Articles >  An accurate and fast pattern localization algorithm for automated visual inspection

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    Title: An accurate and fast pattern localization algorithm for automated visual inspection
    Authors: Shang-Hong Lai;Ming Fang
    Teacher: 賴尚宏
    Date: 1999
    Publisher: Elsevier
    Relation: REAL-TIME IMAGING,Volume 5,Issue 1,Pages 3-14,FEB 1999
    Keywords: Pattern localization
    Newton method
    Iterative process
    Experimental result
    Optical flow
    Visual information
    Pattern recognition
    Image processing
    Fast algorithm
    Real image
    Taylor series
    Abstract: Accurate and efficient localization of patterns from noisy images is very crucial in automated visual inspection. In this paper we present an accurate, efficient and robust algorithm for 2D pattern localization based on a modified optical flow constraint, which is derived from the first-order Taylor series approximation of the generalized brightness assumption. Our algorithm allows for large global illumination changes since this factor is explicitly modeled on the generalized brightness assumption. The proposed pattern localization algorithm is based on an energy minimization approach, with the energy function being defined as a weighted sum of the modified optical flow constraints at selected locations with reliable constraints. This location selection is facilitated by a reliability measure given in this paper. The energy minimization is accomplished via an efficient Newton-like iterative algorithm, which has been proved to be reliable for precise localization problems with a rough initial guess from our experiments. Experimental results on some real images and the corresponding simulated images are given to demonstrate the accuracy, efficiency and robustness of our algorithm.
    Appears in Collections:[Department of Computer Science] CS Journal / Magazine Articles

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