A novel sub-pixel edge detection for micro-parts manipulation

This paper presents a novel sub-pixel edge detection and center localization algorithm to improve the resolution and accuracy for micro-assembly systems. There are three steps to realize the algorithm. First the invariant moment is used to describe the feature of micro-parts and the edge of the micro-parts is extracted at pixel level by using Canny operator. Secondly, the image information of gradient direction from the edge neighborhood is employed to locate the edge of the micro-parts at sub-pixel level. Last, apply least squares ellipse to get the position of the parts centers. Experiment results show that the presented algorithm could achieve higher location accuracy and consume less time.

[1]  Chein-I Chang,et al.  Fully constrained least squares linear spectral mixture analysis method for material quantification in hyperspectral imagery , 2001, IEEE Trans. Geosci. Remote. Sens..

[2]  Y. Sheng,et al.  Orthogonal Fourier–Mellin moments for invariant pattern recognition , 1994 .

[3]  Rama Chellappa,et al.  Hybrid Detectors for Subpixel Targets , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Manfred H. Hueckel An Operator Which Locates Edges in Digitized Pictures , 1971, J. ACM.

[5]  Moon Gi Kang,et al.  Super-resolution image reconstruction: a technical overview , 2003, IEEE Signal Process. Mag..

[6]  W.J. Zhang,et al.  Automatic Optical Defect Inspection and Dimension Measurement of Drill Bit , 2006, 2006 International Conference on Mechatronics and Automation.

[7]  Ming-Kuei Hu,et al.  Visual pattern recognition by moment invariants , 1962, IRE Trans. Inf. Theory.

[8]  Ieee Xplore,et al.  IEEE Transactions on Pattern Analysis and Machine Intelligence Information for Authors , 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  John P. Kerekes,et al.  Spectral imaging system analytical model for subpixel object detection , 2002, IEEE Trans. Geosci. Remote. Sens..

[10]  Chaur-Chin Chen Improved moment invariants for shape discrimination , 1993, Pattern Recognit..

[11]  Gary A. Shaw,et al.  Hyperspectral subpixel target detection using the linear mixing model , 2001, IEEE Trans. Geosci. Remote. Sens..

[12]  Manfred H. Hueckel A Local Visual Operator Which Recognizes Edges and Lines , 1973, JACM.

[13]  Dimitris Anastassiou,et al.  Subpixel edge localization and the interpolation of still images , 1995, IEEE Trans. Image Process..