基于JETSON TX2的快速二值图像连通区域标记算法  

Fast Connected Area Labeling Algorithm on Binary Images Based on JETSON TX2

作　　者：吴咏辉 甘万兵 陈天赋 邵光保 李中伟[1] 钟凯[1] 陈然 WU Yonghui;GAN Wanbing;CHEN Tianfu;SHAO Guangbao;LI Zhongwei;ZHONG Kai;CHEN Ran(State Key Laboratory of Material Processing and Die & Mould Technology,Huazhong University of Science and Technology,Wuhan 430074,China;Hubei Trairing Forging Co.,Ltd.,Xiangyang 441700,China)

机构地区：[1]华中科技大学材料成形与模具技术国家重点实验室,湖北武汉430074 [2]湖北三环锻造有限公司,湖北襄阳441700

出　　处：《新技术新工艺》2019年第5期48-52,共5页New Technology & New Process

摘　　要：为了提高二值图像连通区域标记算法速度,提出了一种基于JETSONTX2的快速二值图像连通区域标记算法。首先,创建与二值图像相同维度的标记矩阵,通过第1步扫描对标记矩阵中的非零元素设置初始化标号,再利用8邻域连通模板获取当前标号下对应邻域最小标号值;然后,通过第2步扫描寻找与判别模型相同的情况,合并等价根元素,并利用原子操作确保根元素的修改正确;最后,利用寻根操作对标记矩阵中的所有非零元素进行一次性修改。试验结果表明,该算法充分利用了GPU的并行计算能力,在处理高分辨率以及多连通域时较常见的CPU串行算法最高达到108倍的加速,与现有的GPU算法相比最高达到8倍的加速。In order to improve the speed of connected area labeling of binary image, a fast connected area labeling algorithm on binary image based on JETSON TX2 was proposed. Firstly, a labeling matrix with the same dimension as binary image was created, the labeling was initialized for each non-zero element through the first step scan, and then the minimum labeling value of corresponding neighborhood under the current pixel was obtained by using mask for eight-connected connectivity. Then, through the second step scanning, found the same situation as the discriminant model and merged the equivalent root elements, and used atomic operation to ensure that the modification of the root elements was correct. Finally, all non-zero elements in the labeling matrix were modified one-time by root-finding operation. The experimental results showed that the algorithm made full use of the parallel computing power of GPU, when dealing with high resolution and multi-connected components, the speed of this algorithm was 108 times faster than that of the existing CPU algorithm, and was 8 times faster than that of the existing GPU algorithm.

关 键 词：GPU 二值图像 连通区域标记 判别模型 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]