光学精密工程
光學精密工程
광학정밀공정
OPTICS AND PRECISION ENGINEERING
2010年
2期
464-469
,共6页
高春甫%唐可洪%胡庆玉%程丽丽%赵丁选
高春甫%唐可洪%鬍慶玉%程麗麗%趙丁選
고춘보%당가홍%호경옥%정려려%조정선
双目立体视觉%机械手%匹配算法%姿态识别
雙目立體視覺%機械手%匹配算法%姿態識彆
쌍목입체시각%궤계수%필배산법%자태식별
binocular stereo vision%manipulator%match algorithm%attitude recognition
为了提高机械手姿态识别的精度,提出了区域边缘线段立体匹配算法.该算法利用图像中包含边缘线段区域的颜色特性和边缘线段的几何特征进行线段匹配,其中,区域的颜色特征包括边缘线段的左右颜色和梯度方向,边缘线段的几何特征包括长度、方向和角度.由于充分利用了图像提供的颜色信息,特别是颜色梯度方向信息,使得边缘线段的匹配不仅依靠其自身的几何特征(如长度,方向和位置),而且依靠直线段所在图像区域的所有信息.因此,匹配的判据可以做得更准确.使用该算法进行机械手姿态识别实验,结果验证了该算法能够在复杂背景下识别机械手的姿态,识别精度高,其相对误差达到1.7%,该结果满足机械手在姿态识别中的精度要求.
為瞭提高機械手姿態識彆的精度,提齣瞭區域邊緣線段立體匹配算法.該算法利用圖像中包含邊緣線段區域的顏色特性和邊緣線段的幾何特徵進行線段匹配,其中,區域的顏色特徵包括邊緣線段的左右顏色和梯度方嚮,邊緣線段的幾何特徵包括長度、方嚮和角度.由于充分利用瞭圖像提供的顏色信息,特彆是顏色梯度方嚮信息,使得邊緣線段的匹配不僅依靠其自身的幾何特徵(如長度,方嚮和位置),而且依靠直線段所在圖像區域的所有信息.因此,匹配的判據可以做得更準確.使用該算法進行機械手姿態識彆實驗,結果驗證瞭該算法能夠在複雜揹景下識彆機械手的姿態,識彆精度高,其相對誤差達到1.7%,該結果滿足機械手在姿態識彆中的精度要求.
위료제고궤계수자태식별적정도,제출료구역변연선단입체필배산법.해산법이용도상중포함변연선단구역적안색특성화변연선단적궤하특정진행선단필배,기중,구역적안색특정포괄변연선단적좌우안색화제도방향,변연선단적궤하특정포괄장도、방향화각도.유우충분이용료도상제공적안색신식,특별시안색제도방향신식,사득변연선단적필배불부의고기자신적궤하특정(여장도,방향화위치),이차의고직선단소재도상구역적소유신식.인차,필배적판거가이주득경준학.사용해산법진행궤계수자태식별실험,결과험증료해산법능구재복잡배경하식별궤계수적자태,식별정도고,기상대오차체도1.7%,해결과만족궤계수재자태식별중적정도요구.
A region-margin line segment stereo matching algorithm is proposed to improve the posture recognition precision of a manipulator. The color characteristics of the region and the geometric characteristics of margin line segment included in the image are used to realize an integrate matching,among which the former contains the color and margin line segment,and the latter contains lengths,directions and angles.By making full use of the information of color included in the image ,especially the gradient direction information, this algorithm makes the line segment matching depend on the all information of the image area,not only on its geometric characteristics, such as lengths,directions and angles. Therefore,the criterion of the matching is more accurate than those of traditional algorithms.A posture recognition experiment for a manipulator is undertaken,obtained results validate that the algorithm could recognize the posture of manipulator in higher accuracy in a complicated background, and the relative error reaches 1.7%,which meets the requirements of the attitude recognition of manipulators for the precision.