Title :
Pattern Recognition by Cluster Accumulation
Author :
Bhatia, Amit ; Bilbro, Griff L. ; Snyder, Wesley E.
Author_Institution :
Univ. of California, San Diego, CA, USA
Abstract :
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.
Keywords :
correlation methods; feature extraction; object detection; pattern clustering; shape recognition; PRCA method; cluster accumulation; cluster shape distortion; dimensionality reduction; feature selection; geometric features; normalized cross correlation; object detection; pattern recognition; radiometric features; Clustering algorithms; Computer vision; Intelligent vehicles; Layout; Lighting; Pattern recognition; Pixel; Radiometry; Robustness; USA Councils; Clustering; Pattern Recognition;
Conference_Titel :
Intelligent Vehicles Symposium (IV), 2010 IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-7866-8
DOI :
10.1109/IVS.2010.5547958
