Name: Skin Colour Segmentation Using Bivariate Pearsonian Mixture Models (en Inglés)
Price: 284634.00 COP
Availability: InStock
Author: Jagadesh, B. N.
ISBN: 9786138941323

portada Skin Colour Segmentation Using Bivariate Pearsonian Mixture Models (en Inglés)

Skin Colour Segmentation Using Bivariate Pearsonian Mixture Models (en Inglés)

Formato

Libro Físico

Autor

B. N. Jagadesh

Editorial

Scholars' Press

Idioma

Inglés

N° páginas

176

Encuadernación

Tapa Blanda

Dimensiones

22.9 x 15.2 x 1.0 cm

Peso

0.27 kg.

ISBN13

9786138941323

Categorías

Tecnología de la información: cuestiones generales

Skin Colour Segmentation Using Bivariate Pearsonian Mixture Models (en Inglés)

B. N. Jagadesh (Autor) · Scholars' Press · Tapa Blanda

Libro Nuevo Importado

Envío: 21 a 25 días háb.

$ 569.268$ 284.634

-50%

Costos de importación incluídos en el precio ✅

Libro Nuevo

Quedan 10 unidades

$ 284.634

¡Envío Gratis! Llega entre el 19 Ago y el 26 Ago a Bogota, Cundinamarca. Seleccionar ubicación

Agregar a lista de deseos

Reseña del libro "Skin Colour Segmentation Using Bivariate Pearsonian Mixture Models (en Inglés)"

Skin segmentation deals with identification of skin regions from an image for effective analysis. Skin segmentation is an important activity in many real time systems, dealing with human computer interactions. Skin colour segmentation is a complex task involving several compound activities. Several authors developed various segmentation techniques with the assumption that the feature vector associated with the skin region follows a Gaussian or mixture of Gaussian distribution. The skin colour segmentation methods serve well only when the feature vector consists of hue and saturation values of the pixels in the skin image region which are symmetric and meso-kurtic. However, in many images the feature vector may not be symmetric and meso-kurtic. To have an accurate skin colour segmentation it is needed to have skin colour segmentation methods based on non Gaussian bivariate mixture distributions. Hence, this thesis deals with development and analysis of skin colour segmentation methods based on bivariate Pearsonian mixture distributions for different races of human skin namely, African, Asian and European separately.