Pattern Recognition by Cluster Accumulation

When objects in images are small or blurred enough, geometric features are inadequate for reliable pattern recognition. We introduce the Pattern Recognition by Cluster Accumulation (PRCA) method to show that pattern recognition performance can be improved in this situation by using radiometric features for object detection. In addition, PRCA uses clustering to provide feature selection and dimensionality reduction. It uses accumulation to provide robustness against translation, rotation, cluster shape distortion, and inappropriate splitting or merging of clusters. We find that PRCA performs faster than normalized cross correlation and faster than mutual information methods. 1

[1]  Carlo Tomasi,et al.  Image Similarity Using Mutual Information of Regions , 2004, ECCV.

[2]  David G. Stork,et al.  Pattern Classification , 1973 .

[3]  Loris Nanni,et al.  Cluster-based pattern discrimination: A novel technique for feature selection , 2006, Pattern Recognit. Lett..

[4]  Hans-Peter Kriegel,et al.  A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.

[5]  Paul A. Viola,et al.  Alignment by Maximization of Mutual Information , 1997, International Journal of Computer Vision.

[6]  Max A. Viergever,et al.  Image registration by maximization of combined mutual information and gradient information , 2000, IEEE Transactions on Medical Imaging.

[7]  Azriel Rosenfeld,et al.  Picture Processing by Computer , 1969, CSUR.

[8]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[9]  Daniel Rueckert,et al.  Non-rigid registration using higher-order mutual information , 2000, Medical Imaging.

[10]  Guy Marchal,et al.  Multimodality image registration by maximization of mutual information , 1997, IEEE Transactions on Medical Imaging.

[11]  Cordelia Schmid,et al.  Indexing Based on Scale Invariant Interest Points , 2001, ICCV.

[12]  Azriel Rosenfeld,et al.  Two-Stage Template Matching , 1977, IEEE Transactions on Computers.

[13]  J. Howard Johnson,et al.  Analysis of Image Forming Systems , 1985 .

[14]  Wesley E. Snyder,et al.  Global registration of overlapping images using accumulative image features , 2010, Pattern Recognit. Lett..

[15]  Xiaoyan Zhu,et al.  A novel registration method that incorporates template matching and mutual information , 2009, 2009 IEEE International Conference on Automation and Logistics.