华南理工大学学报(自然科学版)
華南理工大學學報(自然科學版)
화남리공대학학보(자연과학판)
JOURNAL OF SOUTH CHINA UNIVERSITY OF TECHNOLOGY(NATURAL SCIENCE EDITION)
2010年
1期
65-69,86
,共6页
贴片元件%亚像素%视觉检测%快速傅里叶变换%边缘检测%拟合
貼片元件%亞像素%視覺檢測%快速傅裏葉變換%邊緣檢測%擬閤
첩편원건%아상소%시각검측%쾌속부리협변환%변연검측%의합
chip component%subpixel%vision inspection%fast Fourier transform%edge detection%fitting
为了实现贴片元件的自动检测,提出了一种基于视觉的贴片元件几何特征参数检测方法.首先采用最大外接矩形法实现元件的粗定位及确定边缘的分割点,并采用Canny和Zernike矩边缘检测算子实现边缘的精确定位.然后,利用分割点将边缘分割成4部分,分别进行直线和圆弧拟合,得到其精确值.同时,利用快速傅里叶变换后的图像特征,实现端面图像中条纹方向的判定.实验中测得亚像素边缘点的定位精度为0.03像素,直线拟合精度为0.03像素,圆弧拟合精度为0.05像素,端面条纹判断的准确率为100%.实验结果表明:文中提出的检测方法能很好地满足贴片元件自动视觉检测稳定可靠、精度高及实时性强的要求.
為瞭實現貼片元件的自動檢測,提齣瞭一種基于視覺的貼片元件幾何特徵參數檢測方法.首先採用最大外接矩形法實現元件的粗定位及確定邊緣的分割點,併採用Canny和Zernike矩邊緣檢測算子實現邊緣的精確定位.然後,利用分割點將邊緣分割成4部分,分彆進行直線和圓弧擬閤,得到其精確值.同時,利用快速傅裏葉變換後的圖像特徵,實現耑麵圖像中條紋方嚮的判定.實驗中測得亞像素邊緣點的定位精度為0.03像素,直線擬閤精度為0.03像素,圓弧擬閤精度為0.05像素,耑麵條紋判斷的準確率為100%.實驗結果錶明:文中提齣的檢測方法能很好地滿足貼片元件自動視覺檢測穩定可靠、精度高及實時性彊的要求.
위료실현첩편원건적자동검측,제출료일충기우시각적첩편원건궤하특정삼수검측방법.수선채용최대외접구형법실현원건적조정위급학정변연적분할점,병채용Canny화Zernike구변연검측산자실현변연적정학정위.연후,이용분할점장변연분할성4부분,분별진행직선화원호의합,득도기정학치.동시,이용쾌속부리협변환후적도상특정,실현단면도상중조문방향적판정.실험중측득아상소변연점적정위정도위0.03상소,직선의합정도위0.03상소,원호의합정도위0.05상소,단면조문판단적준학솔위100%.실험결과표명:문중제출적검측방법능흔호지만족첩편원건자동시각검측은정가고、정도고급실시성강적요구.
In order to automatically inspect chip components, a vision-based method is proposed to calculate the geometrical parameters of the components. In this method, first, the coarse location of chip components and the edge point sorting are realized by means of the maximum external rectangle method, and the precise location of the edge is implemented by using the Canny operator and the Zernike moment operator. Next, the edge points are sorted into 4 parts according to sorting points, which are then fitted respectively via line and arc fittings to obtain the corresponding accurate values. Moreover, the stripe direction of the transverse image of chip components is correctly judged according to the image characteristics obtained via the fast Fourier transform (FFT). Finally, an experiment is carried out, with a subpixel location precision of 0.03 pixel, a line fitting precision of 0.03 pixel, an arc fitting precision of 0.05 pixel and a stripe direction accuracy of the transverse image of 100% being obtained. The results indicate that the proposed inspection method is of strong stability, high precision and excellent real-time perfor-mance, which is helpful in the automatic vision-based inspection of chip components.