نتایج جستجو برای: color system and feature vector
تعداد نتایج: 17179243 فیلتر نتایج به سال:
Compared with the two-dimensional media, the image depth of three-dimensional media can offer more intuitive and real scenes to the audience for feeling. But with the development of 3D display machines, there is a serious contradiction between the rapid of the 3D display machines and the lack of resources for the machines. To solve the problem, proposed an efficient image depth extraction metho...
This paper deals with processing of wireless capsule endoscopy (WCE) images from gastrointestinal tract, by extracting textural features and developing a suitable classifier to recognize as a normal or abnormal /tumor image. Images obtained from WCE are prone to noise. To reduce the noise, filtration technique is used. The quality of the filtered image is degraded, so to enhance the quality of ...
in this thesis, we consider a mathematical model of cancer with completely unknown parameters. we study the stability of critical points which are biologically admissible. then we consider a control on the system and introduce situations at which solutions are attracted to critical points and so the cancer disease has auto healing. the lyapunov stability method is used for estimating the un...
Image classification is one of the most important tasks of remote sensing information processing used for object recognition. In this paper, a novel scheme is proposed to improve the accuracy of hyperspectral image classification by amalgamating multiple feature vector sets and ensemble methods with different classifiers. Extracting the texture, color and object features of the satellite images...
To reason about the meaning of an image, useful information should be provided with that image; however, images often contain little to no textual information about the objects they are depicting, which is the precise reason why there is a need for CBIR systems that exploit only the correlations present in the raw pixel data. In this paper, we proposed a new type of image feature, which consist...
This paper describes WIPETM Wavelet Image Pornogra phy Elimination an algorithm capable of classifying an image as ob jectionable or benign The algorithm uses a combination of Daubechies wavelets normalized central moments and color histograms to provide semantically meaningful feature vector matching so that comparisons be tween the query image and images in a pre marked training set can be pe...
In this paper we address the issue of image database retrieval based on color using various vector distance metrics. Our system is based on color segmentation where only a few representative color vectors are extracted from each image and used as image indices. These vectors are then used with vector distance measures to determine similarity between a query color and a database image. We test n...
This paper describes WIPETM (Wavelet Image Pornography Elimination), an algorithm capable of classifying an image as objectionable or benign. The algorithm uses a combination of Daubechies' wavelets, normalized central moments, and color histograms to provide semantically-meaningful feature vector matching so that comparisons between the query image and images in a pre-marked training set can b...
In this paper, we describe the system jointly developed by IBM Research and Columbia University for video copy detection and multimedia event detection applied to the TRECVID-2010 video retrieval benchmark. A. Content-Based Copy Detection: The focus of our copy detection system this year was fusing three types of complementary fingerprints: a keyframe-based color correlogram, SIFTogram (bag of ...
The choice of an SVM kernel corresponds to the choice of a representation of the data in a feature space and, to improve performance, it should therefore incorporate prior knowledge such as known transformation invariances. We propose a technique which extends earlier work and aims at incorporating invariances in nonlinear kernels. We show on a digit recognition task that the proposed approach ...
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