Edge Detection in Range Images Based on Scan Line Approximation

In this paper we present a novel edge detection algorithm for range images based on a scan line approximation technique. Compared to the known methods in the literature, our algorithm has a number of advantages. It provides edge strength measures that have a straightforward geometric interpretation and supports a classification of edge points into several subtypes. We give a definition of optimal edge detectors and compare our algorithm to this theoretical model. We have carried out extensive tests using real range images acquired by four range scanners with quite different characteristics. Using a simple contour closure technique, we show that our edge detection method is able to achieve a complete range image segmentation into regions. This edge-based segmentation approach turns out to be superior to many region-based methods with regard to both segmentation quality and computational efficiency. The good results that were achieved demonstrate the practical usefulness of our edge detection algorithm.

[1]  Paul J. Besl,et al.  Surfaces in Range Image Understanding , 1988, Springer Series in Perception Engineering.

[2]  Horst Bunke,et al.  Comparing Curved-Surface Range Image Segmenters , 1998, ICCV.

[3]  Theodosios Pavlidis,et al.  Segmentation of Plane Curves , 1974, IEEE Transactions on Computers.

[4]  Anil K. Jain,et al.  A system for 3D CAD-based inspection using range images , 1995, Pattern Recognit..

[5]  James George Dunham,et al.  Optimum Uniform Piecewise Linear Approximation of Planar Curves , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Andrew W. Fitzgibbon,et al.  An Experimental Comparison of Range Image Segmentation Algorithms , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Jake K. Aggarwal,et al.  Model-based object recognition in dense-range images—a review , 1993, CSUR.

[8]  F. M. Wahl,et al.  Fast and robust range data acquisition in a low-cost environment , 1990, ISPRS International Conference on Computer Vision and Remote Sensing.

[9]  Horst Bunke,et al.  Range Image Segmentation: Adaptive Grouping of Edges into Regions , 1998, ACCV.

[10]  Anil K. Jain,et al.  Reconstruction and Boundary Detection of Range and Intensity Images Using Multiscale MRF Representations , 1996, Comput. Vis. Image Underst..

[11]  Y. J. Tejwani,et al.  Robot vision , 1989, IEEE International Symposium on Circuits and Systems,.

[12]  Frank Ade,et al.  Grasping Unknown Objects , 1994, Modelling and Planning for Sensor Based Intelligent Robot Systems.

[13]  Xiaoyi Jiang.  Optimality Analysis of Edge Detection Algorithms for Range Images , 1997, ICIAP.

[14]  Prasanna G. Mulgaonkar,et al.  Understanding Object Configurations using Range Images , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Francois Blais,et al.  Detection of depth and orientation discontinuities in range images using mathematical morphology , 1990, [1990] Proceedings. 10th International Conference on Pattern Recognition.

[16]  Hon-Son Don,et al.  Roof Edge Detection: A Morphological Skeleton Approach , 1992, Advances in Machine Vision.

[17]  Bruce G. Batchelor,et al.  Edge-Region-Based Segmentation of Range Images , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Han Wang,et al.  Second-order implicit polynomials for segmentation of range images , 1996, Pattern Recognit..

[19]  Xiaoming Zhu,et al.  Extracting Polyhedral Models From A Range Image: A Hybrid Approach , 1993, Computer Vision: Systems, Theory and Applications.

[20]  Geoff A. W. West,et al.  Salience Distance Transforms , 1995, CVGIP Graph. Model. Image Process..

[21]  D. Mintz.  Robust consensus based edge detection , 1994 .

[22]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[23]  Sugata Ghosal,et al.  Detection of composite edges , 1994, IEEE Trans. Image Process..

[24]  Ramesh C. Jain,et al.  Three-dimensional object recognition , 1985, CSUR.

[25]  Nasser Kehtarnavaz,et al.  A framework for estimation of motion parameters from range images , 1989, Comput. Vis. Graph. Image Process..

[26]  Gérard G. Medioni,et al.  Refining edges detected by a LoG operator , 1990, Comput. Vis. Graph. Image Process..

[27]  Sugata Ghosal,et al.  Segmentation of range images: an orthogonal moment-based integrated approach , 1993, IEEE Trans. Robotics Autom..

[28]  Jake K. Aggarwal,et al.  Surface Correspondence and Motion Computation from a Pair of Range Images , 1996, Comput. Vis. Image Underst..

[29]  Svetha Venkatesh,et al.  Dynamic Threshold Determination by Local and Global Edge Evaluation , 1995, CVGIP Graph. Model. Image Process..

[30]  Peter E. Hart,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[31]  Terry Caelli,et al.  Computation of Surface Geometry and Segmentation Using Covariance Techniques , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[32]  Arun K. Sood,et al.  Range image segmentation combining edge-detection and region-growing techniques with applications sto robot bin-picking using vacuum gripper , 1990, IEEE Trans. Syst. Man Cybern..