نتایج جستجو برای: color system and feature vector
تعداد نتایج: 17179243 فیلتر نتایج به سال:
In image classification, the common texture-based methods are based on image gray levels. However, the use of color information improves the classification accuracy of the colored textures. In this paper, we extract texture features from the natural rock images that are used in bedrock investigations. A Gaussian bandpass filtering is applied to the color channels of the images in RGB and HSI co...
Feature Extraction is the process to extract image features to a distinguishable extent. Information extracted from images such as color, texture and shape are known as feature vectors. Using multiple feature vectors to describe an image during retrieval process increases the accuracy when compared to the retrieval using single feature vector. The objective of this paper is to analyze the perfo...
In this thesis we propose a standardized method for extracting illumination-invariant images and a novel approach for classifying textures. Experiments are also extended to include object classification using the proposed methods. The illumination-invariant image is a useful intrinsic feature latent in color image data. Existing methods of extracting the invariant image are dependent upon the c...
We propose a novel histogram generation technique using the HSV color space. The histogram retains a perceptually smooth color transition that enables us to do a window-based comparison of feature vectors for the purpose of effective retrieval of similar images from very large databases. During retrieval, we use a vector cosine distance measure for the ordering of image feature vectors. This di...
We propose a novel histogram generation technique using the HSV color space. The histogram retains a perceptually smooth color transition that enables us to do a window-based comparison of feature vectors for the purpose of effective retrieval of similar images from very large databases. During retrieval, we use a vector cosine distance measure for the ordering of image feature vectors. This di...
One of the most common ways of communication in deaf community is sign language recognition. This paper focuses on the problem of recognizing Arabic sign language at word level used by the community of deaf people. The proposed system is based on the combination of Spatio-Temporal local binary pattern (STLBP) feature extraction technique and support vector machine classifier. The system takes a...
Content-based retrieval requires the choice of distance functions for determining inter-image distances. Distance functions considered to be desirable for computing inter-image distances are often too expensive, computationally, to be used for on-line retrieval from large image databases. In this paper, we propose a generic and eecient content-based image retrieval architecture where the origin...
This paper proposes a robust tracking method which concatenates appearance and geometrical features to re-identify human in non-overlapping views. A uniformly-partitioning method is proposed to extract local HSV(Hue, Saturation, Value) color features in upper and lower portion of clothing. Then adaptive principal view selecting algorithm is presented to locate principal view which contains maxi...
Skin color segmentation by a block histogram-based Support Vector Machine (SVM) is proposed in this paper. The color model used is the Hue-Saturation (HS) model. Color information is represented by histogram of a block image on the HS space. To represent histogram information as accurately as possible, an irregular quantization partition approach on HS space is proposed. Histogram information o...
Feature detection and pattern matching play an important role in visualization. Originally developed for images and scalar fields, pattern matching methods become increasingly interesting for other applications, e.g., vector fields. To apply pattern matching to vector fields the basic concepts of convolution and fast Fourier transform (FFT) have to be generalized to vector fields. A formalism s...
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