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Two significant problems in content based retrieval methods are (1) Accuracy: most of the current content based image retrieval methods have not been quantitatively compared nor benchmarked with respect to accuracy and (2) Efficiency: image database search methods must be analyzed for their computational efficiency and interrelationships. We assert that the accuracy problem is due to the generality of the applications involved. In the current systems, the goal of the user is not clear, which results in difficulties in creating ground truth. In this paper, we quantitatively compare and evaluate four fundamentally different methods for image copy location, namely, optimal keys, texture, projection, and template methods in a large portrait database. We discuss some important theoretical interrelationships, computational efficiency, and accuracy with respect to real noise experiments.

Temporally persistent spatial patterns in the electroencephalogram (EEG) are extracted using the Karhunen-Loeve transformation (KLT). Three basic patterns are shown to be sufficient to account for more than 94% of the variance in a 1.0 s segment of the EEG from both a normal individual and a patient with a malignant brain tumor. These patterns interpolated to form topographic maps, reveal what appear to be important spatial characteristics of the EEG. The results suggest that the method may be extremely valuable not only for the reduction of the data collected during electroencephalography but also for delineating spatially independent brain electrical sources underlying the EEG…