CAJ | 학술논문

先进电子制造生产中经常要对PCB板元件进行检测与识别,介绍了一种基于图像模板匹配算法的PCB板元件自动快速检测方法.从检测速度和准确度出发,首先提出了一种图像相似性度量参数指标,并提出一种利用并行混沌算法融合单纯形的算法,来优化搜索图像相似性,给出了算法实现的全过程.用实际拍摄的PCB板元件进行性能测试,验证了该优化算法能提高检测速度.
선진전자제조생산중경상요대PCB판원건진행검측여식별,개소료일충기우도상모판필배산법적PCB판원건자동쾌속검측방법.종검측속도화준학도출발,수선제출료일충도상상사성도량삼수지표,병제출일충이용병행혼돈산법융합단순형적산법,래우화수색도상상사성,급출료산법실현적전과정.용실제박섭적PCB판원건진행성능측시,험증료해우화산법능제고검측속도.
A fast auto-detection method of printed circuit board (PCB) components based on image template matching is introduced in this paper for advanced electronic manufacturing production. In view of practical utilization, a suitable approach of computing the image correlation coefficient is presented. Parallel chaotic optimization algorithms (PCOA) is suggested to optimize the search matching speed, and the whole process of implementing the algorithm is elaborated. To test its performance, the proposed PCOA algorithm is compared with genetic algorithms by using the real picture of PCB components. It is concluded that the proposed approach is more efficient for auto-detection of PCB components.