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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.