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Methods to improve stereo matching algorithm for object segmentation

机译:改进立体匹配算法的对象分割方法

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Up to these days, there are huge amount of stereo matching algorithms and its improved versions. Not sufficient algorithms are proposed to be used in real systems like object recognition not considering time computing and complexity of the algorithm, but only for improving Pixel Error Rate (PER) in disparity image. We used some image processing methods for not only improving PER but also making disparity images good to be used for object segmentation. We used Trellis algorithm which is Dynamic Programming based stereo matching algorithm. Our proposed algorithm shows better results than original Trellis algorithm in qualitative and quantitative manner. Also this algorithm could be implemented in hardware system; it could work in real-time system.
机译:到目前为止,有大量的立体声匹配算法及其改进版本。没有提出将足够的算法用于像对象识别之类的实际系统中,而没有考虑时间计算和算法的复杂性,仅用于提高视差图像中的像素错误率(PER)。我们使用了一些图像处理方法,不仅可以改善PER,而且可以使视差图像很好地用于对象分割。我们使用了Trellis算法,它是基于动态规划的立体声匹配算法。我们提出的算法在定性和定量方面都比原始的Trellis算法有更好的结果。该算法也可以在硬件系统中实现。它可以在实时系统中工作。

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