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Target characteristic extraction algorithm based on block structure variables

机译:基于块结构变量的目标特征提取算法

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In image processing system, the target recognition is very crucial. An optimized algorithm based on the definition of block is presented. In this algorithm, two structure variables are self-defined to calculate the areas and centroids of targets. The labeling conflicts are resolved by tracking and correcting, which means that if there is a conflict, trace the neighbored blocks and correct the labels of them. Finally, the characteristics of blocks, which have the same label, are accumulated. This method has outstanding advantages in saving memory, compared with Pixel labeling algorithm and Run-length code algorithm. The new algorithm is simple and the results of target characteristics are easy to be analyzed and handled in the following processes.
机译:在图像处理系统中,目标识别非常至关重要。提出了一种基于块定义的优化算法。在该算法中,两个结构变量是自定义的,以计算目标的区域和质心。通过跟踪和纠正解析标记冲突,这意味着如果存在冲突,则跟踪邻近的块并更正它们的标签。最后,积累了具有相同标签的块的特征。该方法在节省存储器方面具有出色的优点,与像素标记算法和运行长度代码算法相比。新算法很简单,易于分析目标特性的结果,并在以下过程中处理。

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