CAJ | 학술논문

针对FPC焊盘表面缺陷，提出一种基于图像处理技术的智能检测方法。文章首先获取无缺陷FPC的平均图像为参考，并采用图像差影法对缺陷定位。接着，引入信息熵概念对FPC焊盘表面的几何形貌、颜色波动性进行量化，实现对纹理特征的量化与提取。通过实验观测得到：缺陷焊盘与无缺陷焊盘在颜色、面积特征上具有明显的区别。因此，检测系统通过焊盘的颜色、面积、纹理特征实现对缺陷的检测。检测准确率高达97．8％，50个焊盘的平均检测时间为300ms。满足在线检测的要求。
침대FPC한반표면결함，제출일충기우도상처리기술적지능검측방법。문장수선획취무결함FPC적평균도상위삼고，병채용도상차영법대결함정위。접착，인입신식적개념대FPC한반표면적궤하형모、안색파동성진행양화，실현대문리특정적양화여제취。통과실험관측득도：결함한반여무결함한반재안색、면적특정상구유명현적구별。인차，검측계통통과한반적안색、면적、문리특정실현대결함적검측。검측준학솔고체97．8％，50개한반적평균검측시간위300ms。만족재선검측적요구。
Aiming at the defects of FPC solder surface,a detection method based on image processing is proposed. Firstly,the average image of no defect FPC is obtained as a reference,and defect’s location can be achieved by image difference method. And then,information entropy is introduced to describe color fluctuation and geometrical morphol-ogy on FPC solder for quantifying and extracting texture feature. The color and area feature can also be used to dis-criminate non-defective and defective solder. So,all the defective solder can be detected according to color,area and texture characteristics. The performance of the proposed defect detection algorithm is finally evaluated on-line testing. The average detection time of 50 solders is 300ms,and the detection accuracy can reach up to 97. 8%. It is very fit for real time detection.