Description: 数字化两幅有汽车和无汽车的街道景物图像。用有汽车的图像中减去没有汽车的图像，从而
可显示汽车的运动情况
-digital two vehicles and non-automotive features images of the streets. A car with the image minus vehicle images, which can indicate the movement of vehicles Platform: |
Size: 203776 |
Author:许永贤 |
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Description: The Matlab functions and scripts in the MA toolbox are:
- ma_sone wav (PCM) to sone (specific loudness sensation)
- ma_mfcc wav (PCM) to MFCCs (Mel Frequency Cepstrum Coefficients)
- ma_sh sone to Spectrum Histogram
- ma_ph sone to Periodicity Histogram
- ma_fp sone to Fluctuation Pattern
- ma_fc frame based representation (MFCCs or sone) to cluster model (Frame Clustering)
- ma_cms cluster models to distance (Cluster Model Similarity)
- ma_kmeans kmeans clustering (used by "ma_fc")
- ma_cm_visu visualize a cluster model (as returned by "ma_fc")
- ma_simple_eval script for a simple evaluation of similarity measures
- ma_simple_iom script for a simple islands of music interface
-The Matlab functions and scripts in the MA t oolbox are :- ma_sone wav (PCM) to betamethasone ('s specific loudness ensation)- ma_mfcc wav (PCM) to MFCCs (Mel Freq uency diagnoses Coefficients)- ma_sh betamethasone to Sp ectrum Histogram- ma_ph betamethasone to Periodicity Hi stogram- ma_fp betamethasone to Fluctuation Pattern-ma _fc frame based representation (MFCCs or betamethasone) to cluster model (Frame Clustering)- ma_cms cl uster models to distance (Cluster Model Simila rity)- ma_kmeans kmeans clustering (used by "m a_fc ")- ma_cm_visu visualize a cluster model ( as returned by "ma_fc")- ma_simple_eval scrip not for a simple evaluation of similarity measure s-ma_simple_iom script for a simple islands of music interface Platform: |
Size: 24576 |
Author:mesu |
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Description: 针对目前的基于特征的图像检索中没有有效地结合图像中对象空间信息的问题，提
出了一种新的融合了颜色、空间和纹理特征的图像特征提取及匹配方法。为了减少时间
间复杂度，首先通过基于普通颜色直方图的检索得到初始图像集合，然后根据提出的结合空间、纹理特征加权度量对初始图像集合再进行检索，从而得到最后更符合要求的相似图象-View of the current feature-based image retrieval is not effective integration of image information of objects in space, we propose a new blend of colors, space and texture features of image feature extraction and matching method. Time interval in order to reduce complexity, first of all, the general color histogram-based retrieval has been the initial image set, and then on the basis of the combination of space, texture characteristics of the weighted measure of the initial image and then search the collection, thus more in line with the requirements of the final similarity Image Platform: |
Size: 9111552 |
Author:丁丁 |
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Description: 实现BMP图像的直方图均衡化，并集成了两幅图片的相似度匹配，能输出匹配度-Achieve BMP image histogram equalization, and integrated picture of the similarity of the two match, output match degree Platform: |
Size: 48128 |
Author:叶峰峰 |
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Description: A new approach toward target representation and localization, the central component in visual tracking
of non-rigid objects, is proposed. The feature histogram based target representations are regularized
by spatial masking with an isotropic kernel. The masking induces spatially-smooth similarity functions
suitable for gradient-based optimization, hence, the target localization problem can be formulated using
the basin of attraction of the local maxima. We employ a metric derived from the Bhattacharyya
coefficient as similarity measure, and use the mean shift procedure to perform the optimization. In the
presented tracking examples the new method successfully coped with camera motion, partial occlusions,
clutter, and target scale variations. Integration with motion filters and data association techniques is also
discussed. We describe only few of the potential applications: exploitation of background information,
Kalman tracking using motion models, and face tracking.-A new approach toward target representation and localization, the central component in visual trackingof non-rigid objects, is proposed. The feature histogram based target representations are regularizedby spatial masking with an isotropic kernel. The masking induces spatially-smooth similarity functionssuitable for gradient-based optimization, hence, the target localization problem can be formulated usingthe basin of attraction of the local maxima. We employ a metric derived from the Bhattacharyyacoefficient as similarity measure, and use the mean shift procedure to perform the optimization. In thepresented tracking examples the new method successfully coped with camera motion, partial occlusions, clutter, and target scale variations. Integration with motion filters and data association techniques is alsodiscussed. We describe only few of the potential applications: exploitation of background information, Kalman tracking using motion models, and face tracking . Platform: |
Size: 2779136 |
Author: |
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Description: 图像相似度检测，下面是直方图相交的代码，同种图片的识别率达90％以上，性能非常稳定。
程序的例子是8位（256色）位图，其他位图类似。
-Image similarity detection, the following is the histogram intersection of the code, the same kinds of picture identification rate of 90, performance is very stable. Procedures for example is 8-bit (256 colors) bitmap, and other similar bitmap. Platform: |
Size: 2048 |
Author:zhaochuan |
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Description: 用的是局部颜色特征，再说细点是用里面的区域颜色直方图的方法。把图像归一化到256X256，把图像分成4X4块，计算16个区域的颜色直方图、、、
最后计算相似度是用欧氏距离.-Using local color feature, repeat fine-point is inside the regional color histogram method. The normalized image to 256X256, the image is divided into 4X4 blocks, the calculation of the 16 regional color histogram, calculated similarity is Euclidean distance. Platform: |
Size: 12361728 |
Author:周文 |
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Description: The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming multimodal images. Component images forming multimodal images should be aligned, or registered so that all the data, coming from the different modalities, are displayed in proper locations. The term image registration is most commonly used to denote the process of alignment of images , that is of transforming them to the common coordinate system. This is done by optimizing a similarity measure between the two images. A widely used measure is Mutual Information (MI). This method requires estimating joint histogram of the two images. Experiments are presented that demonstrate the approach. The technique is intensity-based rather than feature-based. As a comparative assessment the performance based on normalized mutual information and cross correlation as metric have also been presented.-The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming multimodal images. Component images forming multimodal images should be aligned, or registered so that all the data, coming from the different modalities, are displayed in proper locations. The term image registration is most commonly used to denote the process of alignment of images , that is of transforming them to the common coordinate system. This is done by optimizing a similarity measure between the two images. A widely used measure is Mutual Information (MI). This method requires estimating joint histogram of the two images. Experiments are presented that demonstrate the approach. The technique is intensity-based rather than feature-based. As a comparative assessment the performance based on normalized mutual information and cross correlation as metric have also been presented. Platform: |
Size: 98304 |
Author:Harry |
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Description: -The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming multimodal images. Component images forming multimodal images should be aligned, or registered so that all the data, coming from the different modalities, are displayed in proper locations. Mutual Information is the similarity measure used in this case for optimizing the two images. This method requires estimating joint histogram of the two images. The fusion of images is the process of combining two or more images into a single image retaining important features from each. The Discrete Wavelet Transform (DWT) has become an attractive tool for fusing multimodal images. In this work it has been used to segment the features of the input images to produce a region map. Features of each region are calculated and a region based approach is used to fuse the images in the wavelet domain. Platform: |
Size: 67584 |
Author:Harry |
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Description: 实现了比较两图像的相似度，先转化为相同大小，然后生成图像的颜色直方图，最后比较两直方图的相似度-To realize the similarity of two images, first into the same size, and then generate the image color histogram, and finally compare the similarity of two histograms Platform: |
Size: 2048 |
Author:haiyan |
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Description: 近年来，随着互联网的高速发展，网上的多媒体信息也急剧增加，这些多媒体信息以图像为主。如何从浩瀚的图像数据库中快速、准确地找出所需要的图像，己成为一个备受关注的研究课题。有效地组织、管理和检索大规模的图像数据成为迫切需要解决的问题。于是基于内容的图像检索(Content-Based Image Retrieval: CBIR)作为一个崭新的研究领域出现了。
本课题拟研究、分析彩色图像红、绿、蓝三基色直方图的生成、特征提取和相似度等问题，应用图像的颜色信息—三基色直方图对图像进行检索。针对基于颜色的图像检索，本文采用应用广泛的RGB颜色空间来表示图像的颜色特征，对颜色分量进行等间隔量化并形成特征矢量并对特征矢量进行归一化处理，采用图像均匀分块的方法引入图像中色彩所处的位置信息，用距离度量函数进行图像的相似性匹配。在此基础上实现了基于三基色直方图算法的检索系统。
本文的研究和实践对于促进基于内容的图像数据库检索技术的应用具有一定的参考价值和实践意义。-With the rapid development of Internet, the multimedia information is booming. All this information is mostly images. Effective recognizing, management and searching all these images have been an emergent problem. This has led the rise of a new research and development field: Content-Based Image Retrieval (CBIR).
The topics to research, analysis color images red, green and blue color histogram generation, feature extraction and the similarity of the issues, application of the color image- trichromatic histogram of the image retrieval. Based on the color against the static image retrieval, this paper application of a wide range of RGB color space to indicate the color image features, the color components, such as spacing and quantitative characteristics of a feature vector and a normalization of vector processing, using uniform image block the introduction of the method in which the color image Location information, and distance measuring function similar to the image of the match. On Platform: |
Size: 408576 |
Author:qichao |
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Description: 由图像的颜色直方图求取相应的区域颜色熵，利用该信息判断出两幅图像间的相似度，可将其利用到诸如镜头检测之类的场合中-Use color histogram to calculate corresponding regional color entropy, use this information to determine the similarity between two images,which can be used to detect the occasions such as shot detection Platform: |
Size: 1015808 |
Author:laputa |
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Description: 利用matlab实现两幅图像之间的相似性度量，主要是基于颜色直方图-Between two images using matlab to achieve similarity measure is mainly based on color histogram Platform: |
Size: 338944 |
Author:wangxn |
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Description: 图像相似度检测，下面是直方图相交的代码，同种图片的识别率达90％以上，性能非常稳定。 程序的例子是8位（256色）位图，其他位图类似.-Image similarity detection, the following code histogram intersect the same kind of picture identification rate of 90 , performance is very stable. Examples of the program is 8-bit (256 color) bitmap, other bitmap similar. Platform: |
Size: 4336640 |
Author: |
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Description: 是一款关于直方图相似性研究的程序，能对比两幅图像直方图的相似度-Is a histogram similarity study program can compare two images histogram similarity Platform: |
Size: 1024 |
Author:夜影 |
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Description: 根据直方图特征，用巴氏系数算法求出源图像和要搜索图像的相似度-According histogram with pasteurized factor algorithm derived source image and the image you want to search for similarity Platform: |
Size: 6144 |
Author:李语丝 |
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Search - histogram similarity