基于图像处理的手持终端光斑检测方法  

Laser Facula Detection Method of Handheld Terminal Based on Image Processing

作　　者：向景睿 吴维德[1] 刘明杰[2] 周林[2] 龙海莲 周承辉 XIANG Jing-rui WU Wei-de LIU Ming-jie ZHOU Lin LONG Hai-lian ZHOU Cheng-hui(Metering Center, State Grid Sichuan Electric Power Company, Chengdu 610041, China School of Electrical Engineering, Southwest Jiaotong University, Chengdu 610031, China Shenzhen Keymantek Public Limited Company, Shenzhen 518129, China)

机构地区：[1]国网四川省电力公司计量中心,四川成都610041 [2]西南交通大学电气工程学院,四川成都610031 [3]深圳市科曼信息技术股份有限公司,广东深圳518129

出　　处：《测控技术》2017年第7期42-46,共5页Measurement & Control Technology

摘　　要：为完成在现场对智能电能表的用电信息采集,计量现场手持终端得到了快速发展。然而现有手持终端设备激光光斑对位精度和处理速度无法满足使用需求,针对国网公司所使用的手持终端设备,提出一种激光光斑的识别检测方法,可以实现现场手持终端的快速准确定位检测。该方法主要包含图像识别、光斑中心点定位及光斑大小计算3个环节,图像识别通过比较全局阈值算法和局部阈值算法各自的优缺点,最终选择使用Otsu算法对图像进行二值化处理。而光斑中心点定位及大小计算则是在综合考虑光斑识别速率以及准确度后,提出一种定位计算方法。最后通过实例验证,证实该方法能够提升计量现场手持终端检测的准确性和工作效率。In order to collect the power consumption information from smart meter in the field, handheld terminal has been developed rapidly. However, the precision and processing speed of laser facula counterpoint in ex- isting handheld equipment cannot meet the demands. Pointed to a kind of handheld terminal used by SGCC, a new detection method of laser facula which can realize the rapid counterpoint and helps to solve measuring field problems is put forward. This method consists of three parts, including image identification, laser faculacenter location and its size calculation. Through comparing the global threshold algorithm and the local threshold algo- rithm, the Otsu algorithm is the optimum choice of former procedure for image binarization processing. For the other steps, a new computing method of laser facula center location is proposed after considering the speed and accuracy of the counterpoint. The method has been proved to be effective in improving the accuracy and efficiency of the measuring handheld terminal by the instance.

关 键 词：手持终端 激光光斑 图像处理 中心距及大小检测 

分 类 号：TM933[电气工程—电力电子与电力传动]