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Texture segmentation by Pseudo Jacobi -Fourier moments is presented in this paper. Given a window size, moments for each pixel in the image are computed within small local windows, and then texture feature images be obtained by using a nonlinear transducer. Finally, each pixel in the image is classified by K-mean clustering algorithm.
The following topics are dealt with: linear approximation; license plate recognition; color image segmentation; image quantization; wireless video transmission; congestion control; stochastic search; transmembrane helical segments; wavelet transform; semisupervised cluster algorithm; anomaly detection; data privacy; online market information processing; user behavior; particle swarm optimization;...
In this paper, it is described a new unsupervised approach based on wavelet packet transform for texture images segmentation. This transform is able to decompose an image not only from the low frequency parts, but also from the middle-high frequency parts, in which there is a certain amount of texture information. After the extraction of the features, a clustering is carried out, by using an immune-inspired...
Several general-purpose algorithms and techniques have been developed for image segmentation. Since there is no general solution to the image segmentation problem, these techniques often have to be combined with domain knowledge in order to effectively solve an image segmentation problem for a problem domain. This paper presents a comparative study of the basic image segmentation techniques i.e. edge-based,...
This paper presents a novel content-based hidden transmission method for secret data to improve the security and secrecy. In the proposed method, the secret data is encrypted by chaotic map before embedding. Then the cover image is segmented by watershed algorithm and fuzzy c-means clustering. At last we extract the feature of each region and embed the secret data into the cover image according to...
In this paper a fast and robust face segmentation method is presented for various face sizes in an image. The method applies the skin color features extracted in the color spaces and a k-means clustering ensembles. There are three stages are included in the proposed method. The first, the skin-color pixel feature vector included both its position and color information is extracted. For providing fast...
This paper presents a method to design programming system using hybrid techniques represented by soft computing to classify objects from the air photos and satellite images depending on their features with minimum acceptable error. These images usually consist of seven layers, while the work in this research focuses on dealing with three bands (red, green and blue). This paper concerns with classifying...
Microarray imaging is now widely used to monitor the activities of thousands of genes simultaneously in biological samples. While there are a number of methods in use for the quantification of microarray images, barriers still exist towards its feasibility for clinical use. Among them, automated spot segmentation is critical for accurate and high throughput measurements of gene expression levels from...
Image clustering can be viewed as a segmentation problem in which small image patches are grouped together based on their features. Rock texture segmentation is a challenging task since the texture is often nonhomogeneous. In this contribution, the new EM (expectation-maximization) rock textures segmentation framework EMRT is proposed. EMRT has two phases, in the first phase the image is divided into...
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