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Data · dataset · 2016

Face Recognition Using Eigen-Face Implemented On DSP Processor

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This paper focus to develop an automatic face recognition using holistic features extracted that use the globalfeatures represented by low frequency data from face image.

Description

Holistic features are extracted using Eigen-face method where a linear projection technique such as PCA is used to capture the important information in the image. Euclidean distance is used for matching process.

The propose method is tested using a benchmark ORL dataset that has 400 images of 40 persons. Euclidean distanceclassifier is tested using the TMS320C6713 digital signal processor (DSP). The computational time is less compared with the offline simulation using PC based.

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The best recognition rate is 95% when tested using 9 training images and 1 testing image represented with 35 PCA coefficients.

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Inferred from text
Image 75% · Simulation 75%
Provenance · 1 source records, 12 field assertions
SourceKeyLast seenRaw
DataCite10.6084/m9.figshare.3573864.v312 d agoJSON v1
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concepts[method].local:method:simulationenrichment · DataCitekeyword-concept-rules@1.0.0title+description (75%)
concepts[modality].local:modality:imageenrichment · DataCitekeyword-concept-rules@1.0.0title+description (75%)
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