Digital spectral analysis: with applications
Digital spectral analysis: with applications
Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
An optimal algorithm for approximate nearest neighbor searching fixed dimensions
Journal of the ACM (JACM)
Approximate nearest neighbor queries in fixed dimensions
SODA '93 Proceedings of the fourth annual ACM-SIAM Symposium on Discrete algorithms
An Algorithm for Finding Best Matches in Logarithmic Expected Time
ACM Transactions on Mathematical Software (TOMS)
Analysis of an Algorithm for Finding Nearest Neighbors in Euclidean Space
ACM Transactions on Mathematical Software (TOMS)
Optimal Expected-Time Algorithms for Closest Point Problems
ACM Transactions on Mathematical Software (TOMS)
Computer Vision
Shape Indexing Using Approximate Nearest-Neighbour Search in High-Dimensional Spaces
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Comparison of Confidence Measures for Face Recognition
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Fast k-Nearest Neighbor Classification Using Cluster-Based Trees
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Face Processing: Advanced Modeling and Methods
Face Processing: Advanced Modeling and Methods
Face recognition from a single image per person: A survey
Pattern Recognition
Content-based image retrieval from a large image database
Pattern Recognition
Content-Based Image Retrieval Using Shifted Histogram
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
A genetic programming framework for content-based image retrieval
Pattern Recognition
Combining similarity measures in content-based image retrieval
Pattern Recognition Letters
Pattern Recognition, Fourth Edition
Pattern Recognition, Fourth Edition
Enhanced local texture feature sets for face recognition under difficult lighting conditions
IEEE Transactions on Image Processing
RSFDGrC'11 Proceedings of the 13th international conference on Rough sets, fuzzy sets, data mining and granular computing
Nearest neighbor pattern classification
IEEE Transactions on Information Theory
On optimum recognition error and reject tradeoff
IEEE Transactions on Information Theory
Approximative fast nearest-neighbour recognition
Pattern Recognition Letters
Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance
IEEE Transactions on Image Processing
Statistical recognition of a set of patterns using novel probability neural network
ANNPR'12 Proceedings of the 5th INNS IAPR TC 3 GIRPR conference on Artificial Neural Networks in Pattern Recognition
Adaptive video image recognition system using a committee machine
Optical Memory and Neural Networks
Real-time image recognition with the parallel directed enumeration method
ICVS'13 Proceedings of the 9th international conference on Computer Vision Systems
Optical Memory and Neural Networks
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The article is devoted to the problem of image recognition in real-time applications with a large database containing hundreds of classes. The directed enumeration method as an alternative to exhaustive search is examined. This method has two advantages. First, it could be applied with measures of similarity which do not satisfy metric properties (chi-square distance, Kullback-Leibler information discrimination, etc.). Second, the directed enumeration method increases recognition speed even in the most difficult cases which seem to be very important in practical terms. In these cases many neighbors are located at very similar distances. In this paper we present the results of an experimental study of the directed enumeration method with comparison of color- and gradient-orientation histograms in solving the problem of face recognition with well-known datasets (Essex, FERET). It is shown that the proposed method is characterized by increased computing efficiency of automatic image recognition (3-12 times in comparison with a conventional nearest neighbor classifier).