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Erschienen in:
2017 | OriginalPaper | Buchkapitel
Skin-Colored Gesture Recognition and Support Vector Machines-Based Classification of Light Sources by Their Illumination Properties
verfasst von : Shreyasi Bandyopadhyay, Sabarna Choudhury, Riya Ghosh, Saptam Santra, Rabindranath Ghosh
Erschienen in: Computational Intelligence in Data Mining
Verlag: Springer Singapore
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Abstract
The illumination characteristics of light sources can determine whether the light source is a normal or a faulty one. The proposed work is based on moving a platform containing a light source in both horizontal and vertical directions by gesture recognition. The gesture recognition done by Fuzzy C means and snake algorithm-based skin color detection makes the recognition more accurate. The illumination values of the light source are obtained by a webcam. The set of data helps in classification of the state of an unknown light source (normal or faulty) by support vector machines with radial basis function as kernel with a yield of an error rate of about 0.6% marking the efficacy of the system and making the system a novel and sophisticated one.