Accurate Computation of Geometric Moments Using Non-symmetry and Anti-packing Model for Color Images

Yunping Zheng, Yi-Hsin Chang, M. Sarem
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引用次数: 2

Abstract

Accurate computation of geometric moments is very important in computer vision, image processing and pattern recognition. In this paper, inspired by the idea of bit-plane decomposition and accurate computation of geometric moments on binary images, we put forward an accurate and fast algorithm for the computation of geometric moments using Non-symmetry and Anti-packing Model (NAM) for color images, which takes O(N) time where N is the number of all NAM blocks. By taking four color images ‘Lena’, ‘Peppers’, ‘Frog’, and ‘Fish’ as typical test objects, and by comparing our proposed NAM-based accurate algorithm with the popular Binary Tree (BT)-based accurate algorithm for computing the geometric moments, the theoretical and experimental results presented in this paper show that our NAM-based accurate algorithm can significantly improve the execution speed by 43.71%, 41.93%, 41.01%, and 38.63% over the BT-based accurate algorithm in images ‘Lena’, ‘Peppers’, ‘Frog’, and ‘Fish’, respectively. Also, our NAM-based accurate algorithm can significantly improve the average execution speed by 41.32% over the BT-based accurate algorithm. Therefore, in the case of computing lower order moments of color images, our proposed accurate algorithm is much faster than the BT-based accurate algorithm.
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基于非对称和反填充模型的彩色图像几何矩精确计算
几何矩的精确计算在计算机视觉、图像处理和模式识别中具有十分重要的意义。本文利用位平面分解和二值图像几何矩精确计算的思想,提出了一种基于非对称反填充模型(NAM)的彩色图像几何矩精确快速计算算法,该算法耗时O(N),其中N为所有NAM块的个数。以“Lena”、“Peppers”、“Frog”和“Fish”4张彩色图像为典型测试对象,将本文提出的基于nama的精确算法与流行的基于二叉树(Binary Tree, BT)的几何矩计算精确算法进行比较,理论和实验结果表明,在“Lena”图像上,基于nama的精确算法的执行速度比基于BT的精确算法显著提高43.71%、41.93%、41.01%和38.63%。分别是“辣椒”、“青蛙”和“鱼”。基于nama的精确算法比基于bt的精确算法平均执行速度提高了41.32%。因此,在计算彩色图像的低阶矩时,我们提出的精确算法比基于bp的精确算法要快得多。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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