HYPER: A New Approach for the Recognition and Positioning of Two-Dimensional Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition of occluded objects: a cluster-structure algorithm
Pattern Recognition
Partial Shape Recognition Using Dynamic Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Recognition of Curved Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Partial Shape Recognition: A Landmark-Based Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Partial Shape Classification Using Contour Matching in Distance Transformation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition
Characterization of Signals from Multiscale Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Based Detection of Corners of Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detection and estimation of circular arc segments
Pattern Recognition Letters
Recognition of 2D Object Contours Using the Wavelet Transform Zero-Crossing Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Invariant 2D object recognition using the wavelet modulus maxima
Pattern Recognition Letters
Feature extraction using wavelet and fractal
Pattern Recognition Letters
Wavelet-based corner detection technique using optimal scale
Pattern Recognition Letters
Wavelet descriptor of planar curves: theory and applications
IEEE Transactions on Image Processing
Multiscale corner detection by using wavelet transform
IEEE Transactions on Image Processing
Balanced feature matching in probabilistic framework and its application on object localisation
International Journal of Computer Applications in Technology
Automatic measuring system for railroad wheels
International Journal of Computer Applications in Technology
Adaptive method for improvement of human skin detection in colour images
International Journal of Computer Applications in Technology
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Partially occluded object recognition is considered as one of the most difficult problems in machine vision; it has significant importance in industrial environment. In this paper, a 2-D object recognition algorithm applicable for both stand-alone and partially occluded objects is presented. The main contributions are the development of a scale and partial occlusion invariant boundary partition algorithm and a multi-resolution feature extraction algorithm using wavelet. We also implemented a hierarchical matching strategy for feature matching to reduce computational load, but with higher matching accuracy. Experiment results show that the proposed recognition algorithm is robust to similarity transformation and partial occlusion.