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The paper presents color texture segmentation using FCM for color texture segmentation based multi-resolution image fusion. First, a color texture images are decomposed of multi-resolution representation by wavelet transform, adaptive fusion weight value of wavelet coefficients are resolved using PCA, then fused images is formed by inverse transforming and combining all wavelet coefficients, the proposed...
In this paper, we proposed a fuzzy c-means (FCM) cluster based adaptive thresholding segmentation algorithm for color image. The main advantage of this method is that, it does not require a priori knowledge about number of objects in the image. It calculates the threshold values automatically with the help of merging process. The first step of the method is that construct the histograms for each color...
This paper presents a new global thresholding method based on wavelet fusion of color image sub-bands that we used for image segmentation. At first, a color image has been decomposed three sub-bands that R(red), G(green), B(blue) channel. Second, each sub-bands channel has been decomposed by discrete wavelet transform (DWT) to the same resolution. Third, fusion operation is performed on the transformed...
Human face recognition plays an important role in applications such as video surveillance, human computer interface, and face image database management. This paper presents an improved face recognition method for multi-pose face recognition in color images, which addresses the problems of illumination and pose variation. At first, color multi-pose faces image features were extracted based on Gabor...
This paper presents a new unsupervised method based on the Expectation-Maximization (EM) algorithm that we apply for color image segmentation. The method firstly Convert Image from RGB Color Space to HSV Color Space; Secondly we make use of a model of mixture K Gaussians, the Expectation Maximization (EM) formula is used to estimate the parameters of the Gaussian Mixture Model (GMM), which the desired...
In this paper, a color pattern recognition technique that is suitable for multicolor images of bark has been analyzed and evaluated. To extract the bark texture features, Gabor filter the image has been filtered with four orientations and six scales filters, and then the mean and standard deviation of the image output are computed. In addition, the obtained Gabor feature vectors are fed up into radial...
This paper proposed a new method of extracting texture features based on Gabor wavelet in different color space. In addition, the application of these features for bark classification applying radial basis probabilistic network (RBPNN) and SVM (support vector machine) has been used. To extract the bark texture features, Gabor filter the image has been filtered with four orientations and six scales...
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