Isbn: 9786137338933 - fusion technique for robust human skin detection: comparative evaluation with fusion approach (6 resultados)

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Paperback. Condición: Brand New. 132 pages. 8.66x5.91x0.30 inches. In Stock.

Taschenbuch. Condición: Neu. Fusion Technique for Robust Human Skin Detection | Comparative Evaluation with Fusion Approach | Vasudha M. P. | Taschenbuch | 132 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786137338933 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Human skin color provides cue to infer variation in culture, race, health, age, wealth, beauty etc and promotes human recognition. Detection and classification of skin color and non skin color pixels is a challenging task and highly expensive. Human visual system incorporates color opponency. Variation in skin color of an image is caused by camera characteristics, ethnicity, subject appearances, background colors, shadows and motion. In fusion technique we used the product of two features to perform automatic skin detection. The frequency variation in RGB color space is removed before applying LO color and includes Logarithm coding and indexing. The skin threshold value(s) are calculated by using online dynamic approach and elliptical gaussian mixture model with 2D histogram and smoothened densities is used for classifying skin pixels. In our technique we used color image(s) obtained under different illumination conditions, different locations, to obtain single and/or multiple images. The proposed technique (i) reduces computational costs as no training is required, (ii) reduces the false positive ratio and provides comparatively more robust and accurate results in skin detection. 132 pp. Englisch.…

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Human skin color provides cue to infer variation in culture, race, health, age, wealth, beauty etc and promotes human recognition. Detection and classification of skin color and non skin color pixels is a challenging task and highly expensive. Human visual system incorporates color opponency. Variation in skin color of an image is caused by camera characteristics, ethnicity, subject appearances, background colors, shadows and motion. In fusion technique we used the product of two features to perform automatic skin detection. The frequency variation in RGB color space is removed before applying LO color and includes Logarithm coding and indexing. The skin threshold value(s) are calculated by using online dynamic approach and elliptical gaussian mixture model with 2D histogram and smoothened densities is used for classifying skin pixels. In our technique we used color image(s) obtained under different illumination conditions, different locations, to obtain single and/or multiple images. The proposed technique (i) reduces computational costs as no training is required, (ii) reduces the false positive ratio and provides comparatively more robust and accurate results in skin detection.…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Human skin color provides cue to infer variation in culture, race, health, age, wealth, beauty etc and promotes human recognition. Detection and classification of skin color and non skin color pixels is a challenging task and highly expensive. Human visual system incorporates color opponency. Variation in skin color of an image is caused by camera characteristics, ethnicity, subject appearances, background colors, shadows and motion. In fusion technique we used the product of two features to perform automatic skin detection. The frequency variation in RGB color space is removed before applying LO color and includes Logarithm coding and indexing. The skin threshold value(s) are calculated by using online dynamic approach and elliptical gaussian mixture model with 2D histogram and smoothened densities is used for classifying skin pixels. In our technique we used color image(s) obtained under different illumination conditions, different locations, to obtain single and/or multiple images. The proposed technique (i) reduces computational costs as no training is required, (ii) reduces the false positive ratio and provides comparatively more robust and accurate results in skin detection.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 132 pp. Englisch.…