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- W1983177466 abstract "Face recognition has potential applications in surveillance and security systems. Most algorithms proceed by constructing a feature vector, which represents those aspects of the face which vary most between individuals. In general these algorithms locate critical features such as the eyes, nose and mouth, and use a mixture of direct comparison, and spatial distribution of features to identify those candidate images in a large database which match the image currently under analysis. Since pixel intensity comparisons for regions around the eyes are often used to compute a measure of similarity between two images lighting can play a major part in the success of recognition techniques. By using a combination of infrared and white light image information we hope to normalize pixel intensities, reducing the error margin due to variations in lighting conditions. However, the most significant problem with recognition systems is the processing delay required to find a match. Since a high degree of certainty is required in security applications, this increases the level of processing required leading to even greater delays. This paper proposes and evaluates a parallel algorithm for face recognition. The general performance characteristics of the algorithm are analyzed using formal methods to obtain the expected temporal and spatial complexities of the algorithm, and to estimate the speedup that can be achieved. Confirmation of these predictions is provided by implementing the parallel algorithm on an eight processor Sequent Balance shared memory multiprocessor and PRISM/DiST, a multiprocessor simulator." @default.
- W1983177466 created "2016-06-24" @default.
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- W1983177466 date "1998-07-02" @default.
- W1983177466 modified "2023-09-23" @default.
- W1983177466 title "<title>Parallel approach to face recognition using IR images</title>" @default.
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- W1983177466 doi "https://doi.org/10.1117/12.312602" @default.
- W1983177466 hasPublicationYear "1998" @default.
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