基于区域生长的指针式仪表自动识别方法

Automatic Recognition of Analog Measuring Instruments Based on Region Growing

针对复杂多指针式仪表的读数自动识别难度大精度低的问题,提出了一种基于区域生长的指针式仪表自动识别方法.算法主要由基于区域生长的指针提取算法和基于Hit-Miss变换法击中直线或基于最小二乘法拟合直线的指针识别算法所组成.其中,区域生长所需的种子点通过基于差影法的模糊聚类自动选取.实验表明,基于区域生长的指针提取算法有效提取了指针特征,为Hit-Miss变换法和最小二乘法获得良好的指针识别精度奠定了重要基础.整个算法高效快速,能满足实时识别的应用需求.本文首次提出将基于区域生长的图像分割算法运用于指针式仪表识别领域中,丰富了指针式仪表识别的应用方法,获得了良好的识别效果.

Aiming at the difficulty of recogniseing complex multi-pointer instruments, this paper presents an automatic recognition system of analog measuring instruments based on region growing. The whole algorithm consists of pointer extraction algorithm based on region growing method and pointer recognition algorithm based on hit-miss transform method or least square method. Besides, the seeds needed by region growing can automatically obtained by fuzzy clustering based on difference image. Experiments show that, the pointer extraction algorithm based on region growing method effectively extract the features of pointers. And the extraction algorithm lays the foundation for the Hit-Miss transform method and the least square method to obtain good recognition accuracy. The algorithm is fast and efficient, can satisfy the requirements of real-time applications. This paper first applies region growing method of image segmentation to the field of analog measuring instruments recognition, enriches the method of analog measuring instruments recognition, achieved good recognition effect.