Feature Extraction and Matching Using Scale Invariant Feature Transform For Indian Sign Language

Sandeep B. Patil, G. R. Sinha

Abstract


Lack of awareness for deaf people leads to increased
communication gap, misconceptions and superstitions among
deaf and hard hearing community. This paper describes a
method for extracting distinctive features from an image and
performs reliable matching between two images having
different scales. We have shown that the features are invariant
to scale, illumination, clutters and provide robust matching for
recognition. The acquired features are highly distinctive such
that a single feature can be correctly matched with high
probability. The experimental result shows the time constraint
for extracting the SIFT key features for original and scale
changed image. These extracted features are then matched and
percentage accuracy has been determined. The feature
extraction and matching has been implemented over Indian
Sign Language (ISL) biometrics.

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References


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