Computer Science ›› 2016, Vol. 43 ›› Issue (4): 284-289.doi: 10.11896/j.issn.1002-137X.2016.04.058

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Detection and Location on Circular Valve Handle Based on Feature Decomposition and Combination

HE Li-xin, KONG Bin, YANG Jing, XU Yuan-yuan and WANG Bin   

  • Online:2018-12-01 Published:2018-12-01

Abstract: To avoid sample collection,manual labelling and local extremum in the target detection method based on support vector machine or neural network,detection on geometrical feature of the common industrial circular valve handles was transformed into detection on two sub-features,circle and line segments in this paper.Namely,Hough transform is employed to detect circles and lines on an image captured by robot firstly.Only three lines are remained which best correspond to geometrical feature of circular valve handles in the designed algorithms.Then,combing the detected circle,lines and the angles features,the detected circle will be judged whether it is a handle or not.And the positions of inserting robot’s three fingers to operate the handle are obtained.The experiment results indicate that there’s no rigorous requirement for shooting angle and brightness,the circular valve handles can be detected effectively,and the position of inserting robot’s fingers can be calculated accurately by the method.The correct detection and location ratio is 90.7%.

Key words: Circular valve handle,Detection and location,Hough transform,Geometrical feature,Radial line

[1] Yuan Guo-wu,Chen Zhi-qiang,Gong Jian,et al.A Moving Ob-ject Detection Algoirthm Based on a Combination of Optical Flow and Three-Frame Difference[J].Journal of Chinese Computer Systems,2013,4(3):669-671(in Chinese) 袁国武,陈志强,龚健,等.一种结合光流法与三帧差分法的运动目标检测算法[J].小型微型计算机系统,2013,4(3):669-671
[2] Wu Da-peng,Cheng Wei-ping,Yu Sheng-lin.Camshift Object Tracking Algorithm Based on Inter-frame Difference and Motion Prediction[J].Opto-electronic Engineering,2010,7(1):55-60(in Chinese) 邬大鹏,程卫平,于盛林.基于帧间差分和运动估计的Camshift目标跟踪算法[J].光电工程,2010,7(1):55-60
[3] Wang Lu,Wang Lei,Wen Ming,et al.Background subtraction using incremental subspace learning [C]∥IEEE International Conference on Image Processing(ICIP2007).San Antonio.USA:IEEE,2007:45-48
[4] Wei Guo-jian,Hou Zhi-qiang,Li Wu,et al.Object tracking algorithm fused with optical flow detection and template matching[J].Application Research of Computer,2014,1(11):3498-3501(in Chinese) 魏国剑,侯志强,李武,等.融合光流检测与模板匹配的目标跟踪算法[J].计算机应用研究,2014,1(11):3498-3501
[5] Denman S,Chandran V,Sridharan S.An adaptive optical flowtechnique for person tracking systems[J].Pattern Recognition Letters,2007,28(7):1232-1239
[6] Zhang Sheng,Yan Yun-yang,Li Yu-feng.Moving Target Detection Using Fusion of Visual and Thermal Video[J].Computer Science,2015,2(8):86-89,7(in Chinese) 张笙,严云洋,李郁峰.热红外与可见光视频融合的运动目标检测[J].计算机科学,2015,2(8):86-89,127
[7] Yin Wei-chong,Lu Tong.Novel Framework for Multi-view Object Detection throught Combining Multiple Classifiers[J].Computer Science,2013,0(7):266-269(in Chinese) 尹维冲,路通.基于多分类器融合的多视角目标检测算法[J].计算机科学,2013,0(7):266-269
[8] Wang Dao-ming,Lu Chang-hua,Jiang Wei-wei,et al.Study on PSO-based decision-tree SVM multi-class classification method[J].Journal of Electronic Measurement and Instrumentation,2015,9(4):611-615(in Chinese) 王道明,鲁昌华,蒋薇薇,等.基于粒子群算法的决策树 SVM 多分类方法研究[J].电子测量与仪器学报,2015,29(4):611-615
[9] Hsu C,Lin C.A comparison of methods for multiclass support vector machines[J].IEEE Transactions on Neural Networks,2002,13(2):415-425
[10] Zhang M,Ciesielski V.Neural Networks and genetic algorithms for domain independent multiclass object detection[J].International Journal on Computational Intelligence and Applications,2004,4(1):77-108
[11] Lian Ke,Chen Shi-jie,Zhou Jian-ming,et al.Study on GA-based SVM multi-class classification decision-tree optimization algorithm[J].Control and Decision,2009,4(1):7-12(in Chihese) 连可,陈世杰,周建明,等.基于遗传算法的 SVM 多分类决策树优化算法研究[J].控制与决策,2009,24(1):7-12
[12] Zhang Zhao-hui,Liu Yong-xia,Lei Qian.Image Object Detection Based on SC-AdaBoost[J].Computer Science,2015,2(7):309-313(in Chinese) 张朝晖,刘永霞,雷倩.基于SC-AdaBoost的图像目标检测[J].计算机科学,2015,2(7):309-313
[13] Sonka M,Hlavac V,Boyle R.Image Processing,Analysis,and Machine Vision(3rd ed)[M].USA:Nelson Engineering,2007
[14] Atherton T J,Kerbyson D J.Size Invariant Circle Detection[J].Image and Vision Computing,1999,17(11):795-803
[15] Davies E R.Computer & Machine Vision:Theory,Algorithms,Practicalities(4th ed)[M].USA:Academic Press,2012

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