Recognizing polyhedral objects using neural networks

Two different neural networks: the backpropagation (BPNN) and the generalized regression (GRNN) neural networks were used to solve the polyhedral object recognition problem. Some comparisons between these two NNs with the absence and presence of noise-characterized by the absence of significant segments or the presence of spurious ones-were done. The proposed schemes (using either a BPNN or the GRNN) consist of two phases: model building and object recognition. During the model building process, each characteristic view (CV) of the object is described by a feature vector containing the normalized distances from each CV's vertex to the CV's centroid. During the object recognition phase, a set of vectors is used to train the NN. Finally a vector representing one of the object's CVs is presented to the NN to test its performance as a classifier.

[1]  Basil G. Mertzios,et al.  Shape recognition with a neural classifier based on a fast polygon approximation technique , 1994, Pattern Recognit..

[2]  Nikhil R. Pal,et al.  A new shape representation scheme and its application to shape discrimination using a neural network , 1993, Pattern Recognit..

[3]  Su-Shing Chen,et al.  Three-Dimensional Object Recognition Using Range Data , 1989, Other Conferences.

[4]  Charles R. Dyer,et al.  Model-based recognition in robot vision , 1986, CSUR.

[5]  Nirwan Ansari,et al.  Recognizing partially occluded objects by a bidirectional associative memory neural network , 1993 .

[6]  Pong C. Yuen,et al.  Recognition of occluded objects , 1992, Pattern Recognit..

[7]  Donald F. Specht,et al.  A general regression neural network , 1991, IEEE Trans. Neural Networks.

[8]  Nasser M. Nasrabadi,et al.  Object recognition by a Hopfield neural network , 1991, IEEE Trans. Syst. Man Cybern..

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

[10]  Nasser M. Nasrabadi,et al.  Object recognition by a Hopfield neural network , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[11]  Wei-Chung Lin,et al.  A hierarchical multiple-view approach to three-dimensional object recognition , 1991, IEEE Trans. Neural Networks.

[12]  Simone Santini,et al.  Three-dimensional planar-faced object classification with Kohonen maps , 1993 .

[13]  Yoshiaki Shirai,et al.  Object Recognition Using Three-Dimensional Information , 1981, IEEE Transactions on Pattern Analysis and Machine Intelligence.