Description: This handbook presents a thorough overview in 45 chapters from more than 100 renowned experts in the field. It provides the tools to help overcome the problems of video storage, cataloging, and retrieval, by exploring content standardization and other content classification and analysis methods. The challenge of these complex problems make this book a must-have for video database practitioners in the fields of image and video processing, computer vision, multimedia systems, data mining, and many other diverse disciplines. Topics include video segmentation and summarization, archiving and retrieval, and modeling and representation.-This handbook presents a thorough overvie w in 45 chapters from more than 100 renowned expe rts in the field. It provides the tools to help ov ercome the problems of video storage. cataloging, and retrieval. by exploring content standardization and othe r content classification and analysis methods . The challenge of these complex problems make t his book a must-have for video database practit ioners in the fields of image and video processi Vi, computer vision, multimedia systems, data mining. and many other diverse disciplines. Topics inc lude video segmentation and summarization. archiving and retrieval. and modeling and representation. Platform: |
Size: 35815907 |
Author:li ming |
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Description: This handbook presents a thorough overview in 45 chapters from more than 100 renowned experts in the field. It provides the tools to help overcome the problems of video storage, cataloging, and retrieval, by exploring content standardization and other content classification and analysis methods. The challenge of these complex problems make this book a must-have for video database practitioners in the fields of image and video processing, computer vision, multimedia systems, data mining, and many other diverse disciplines. Topics include video segmentation and summarization, archiving and retrieval, and modeling and representation.-This handbook presents a thorough overvie w in 45 chapters from more than 100 renowned expe rts in the field. It provides the tools to help ov ercome the problems of video storage. cataloging, and retrieval. by exploring content standardization and othe r content classification and analysis methods . The challenge of these complex problems make t his book a must-have for video database practit ioners in the fields of image and video processi Vi, computer vision, multimedia systems, data mining. and many other diverse disciplines. Topics inc lude video segmentation and summarization. archiving and retrieval. and modeling and representation. Platform: |
Size: 35815424 |
Author:li ming |
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Description: Classifier4J是一个很好的基于java的分类器,里面有Native bayes和KNN等方法的文本分类.另外还 提供了分词和自动摘要等功能-Classifier4J is a very good java-based classifier, which has Native bayes and KNN methods, such as text classification. It also provides a summary of word segmentation and automatic functions Platform: |
Size: 726016 |
Author:李力 |
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Description: The aim of Optical Character Recognition (OCR) is to classify optical patterns (often contained in a digital image) corresponding to alphanumeric or other characters. The process of OCR involves several steps including segmentation, feature extraction, and classification. This program use Image Processing Toolbox to get it.
For more information, visit: http://www.matpic.com
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Size: 50176 |
Author:ruan |
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Description: 智能运输系统中车牌识别技术得到了广泛应用 , 车牌分割是车牌识别的重要部分。基于彩色图像车牌分割与采用灰度图像车牌分割相比 , 可以有效消除阴影影响 , 同时车牌颜色也是车牌识别的一个参数。颜色分类处理使用特征函数 , 可以减少颜色坐标转换运算 , 提高颜色分类速度。文中详细讨论中国车牌特征 , 给出车牌分割详细步骤。车牌
区域判别采用信息融合技术。车牌倾斜矫正结合车牌倾斜特点 , 提出快速算法。-Intelligent Transport System in the license plate recognition technology has been widely applied, the vehicle registration license plate segmentation is an important part of identification. License Plate Based on Color Image Segmentation and the use of gray-scale image segmentation compared to plate, you can effectively remove the shadow, while the color plates License Plate Recognition is also a parameter. Color classification to deal with the use of characteristic function, can reduce the color coordinate transformation operation, improve the speed of color classification. Discussed in detail the characteristics of the Chinese license plate, license plate segmentation gives the detailed steps. License plate region using information fusion techniques discriminant. License plate license plate combination of slant correction tilt characteristics of fast algorithm. Platform: |
Size: 142336 |
Author:memcpy |
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Description: 此源码可对图像进行Ncut分割，并且集成了特征提取和SVM分类的功能。-This source can be Ncut image segmentation, and integrates the feature extraction and SVM classification function. Platform: |
Size: 34846720 |
Author:leo |
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Description: GSNAKE API provides tools for contour modeling, extraction, detection and classification, based on generalized active contour model (g-snake). GSNAKE consists of a set of objects built in C++, suitable for use in the area of feature extraction, character recognition, motion analysis and etc.
-GSNAKE API provides tools for contour modeling, extraction, detection and classification, based on generalized active contour model (g-snake). GSNAKE consists of a set of objects built in C++, Suitable for use in the area of feature extraction, character recognition, motion analysis and etc. Platform: |
Size: 2981888 |
Author:wzq |
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Description: this a code to segment the color texture using Gabor filter. It uses the initial segmentation using kmeans clustering.-this is a code to segment the color texture using Gabor filter. It uses the initial segmentation using kmeans clustering. Platform: |
Size: 83968 |
Author:sidharth |
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Description: 基于K均值算法和互信息熵差的算法，可以有效地确定分类数,从而该算法对医学图像进行自动优化分割。-K means algorithm based on entropy and mutual information algorithms, can effectively determine the classification number, so that the algorithm for automatic optimization of medical image segmentation. Platform: |
Size: 2048 |
Author:王远 |
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Description: 用来对图像进行分类。Source code for Towards Total Scene Understanding: Classification, Annotation and Segmentation in an Automatic Framework. Computer Vision and Pattern Recognition (CVPR) 2009，Li-Jia Li, Richard Socher and Li Fei-Fei. -Source code for Towards Total Scene Understanding: Classification, Annotation and Segmentation in an Automatic Framework. Computer Vision and Pattern Recognition (CVPR) 2009，Li-Jia Li, Richard Socher and Li Fei-Fei. Platform: |
Size: 31778816 |
Author:qinlei |
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Description: This project describes the work done on the development of an audio segmentation and classification system. Many existing works on audio classification deal with the problem of classifying known homogeneous audio segments. In this work, audio recordings are divided into acoustically similar regions and classified into basic audio types such as speech, music or silence. Audio features used in this project include Mel Frequency Cepstral Coefficients (MFCC), Zero Crossing Rate and Short Term Energy (STE). These features were extracted from audio files that were stored in a WAV format. Possible use of features, which are extracted directly from MPEG audio files, is also considered. Statistical based methods are used to segment and classify audio signals using these features. The classification methods used include the General Mixture Model (GMM) and the k- Nearest Neighbour (k-NN) algorithms. It is shown that the system implemented achieves an accuracy rate of more than 95 for discrete audio classification.-This project describes the work done on the development of an audio segmentation and classification system. Many existing works on audio classification deal with the problem of classifying known homogeneous audio segments. In this work, audio recordings are divided into acoustically similar regions and classified into basic audio types such as speech, music or silence. Audio features used in this project include Mel Frequency Cepstral Coefficients (MFCC), Zero Crossing Rate and Short Term Energy (STE). These features were extracted from audio files that were stored in a WAV format. Possible use of features, which are extracted directly from MPEG audio files, is also considered. Statistical based methods are used to segment and classify audio signals using these features. The classification methods used include the General Mixture Model (GMM) and the k- Nearest Neighbour (k-NN) algorithms. It is shown that the system implemented achieves an accuracy rate of more than 95 for discrete audio classification. Platform: |
Size: 653312 |
Author:kvga |
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Description: 改进的分级多相图像分割模型及其快速实现Improved classification of multi-phase segmentation model and its rapid implementation-Improved classification of multi-phase segmentation model and its rapid implementation Platform: |
Size: 442368 |
Author:shen1052 |
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Description: a book about the segmentation and classification-a book about the segmentation and classification Platform: |
Size: 1448960 |
Author:AKRAME |
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Description: 用于图像的纹理分割，适合用于图像的纹理分割和图像特征分类，并且是基于MATLAB实现的纹理特征分割。-For image texture segmentation, texture suitable for image segmentation and image feature classification, and is based on the MATLAB implementation of the texture features segmentation. Platform: |
Size: 37888 |
Author:王秋燕 |
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Description: Image Texture Classification Using Combined Grey Level Co-Occurrence Probabilities and Support Vector Machines
Texture refers to properties that represent the surface or structure of an object and is defined as something consisting of mutually related elements. The main focus in this study is to do texture segmentation and classification for texture digital images. Grey level co-occurrence probabilities (GLCP) method is being used to extract features from texture image. Gaussian support vector machines (GSVM) have been proposed to do classification on the extracted features. A popular Brodatz texture album had been chosen to test out the result. In this study, a combined GLCP-GSVM shows an improvement over GLCP in terms of classification accuracy. Platform: |
Size: 659456 |
Author:Chetna Kharkar |
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