Description: 随着多媒体、网络技术的迅速发展，图像信息的应用日益广泛，对规模越来越大的图像数据库、可视信息进行有效的管理成为迫切需要解决的问题，灵活、高效、准确的图像检索策略是解决这一问题的关键技术之一。因此，基于内容的图像检索已成为国内外学者研究的主要热点问题，并取得了不少的成果。
本文主要对当今热门的基于内容的图像检索技术进行了研究，重点对它的算法进行研究。在半年的时间里，通过查阅很多相关的资料，并认真学习了基于内容的图像检索的基本理论，特别是深入研究了颜色直方图理论和累加直方图算法，最后在MATLAB平台下编程实现此系统，该系统可以实现基本图像检索的功能，根据用户输入的样本图像来与图像库中的图像进行特征匹配，然后找出与样本图像距离比较小的若干幅图像，并按照图像之间的距离由小到大的顺序显示给用户。
经过对该系统进行反复的调试运行后，该系统所实现的功能基本达到了设计目标，并且运行良好。当用户提供出所要查询的关键图后，系统就可以从用户提供的图像库中检索到与关键图相似的图片并排序返回给用户，达到了预期效果。
-With the rapid development of the multimedia and the network technology, the image information becomes more widely available, increasing the size of the image database, visual information for effective management of an urgent need to address the problem, flexible, efficient and accurate image retrieval strategy solve this problem one of the key technologies. The researchers are so keen on Content-Based Image Retrieval that they have made much progress.
In this paper, today s popular content-based image retrieval technology is analyzed. And it mainly focuses on the research of its algorithm. In a period of half a year, Through access to relevant information and to seriously study the content-based image retrieval of the basic theory, in particular, in-depth study of the color histogram theory and cumulative histogram algorithm. Finally, this system should be implemented under the platform of the MATLAB by programming. In this system, the basic image retrieval functions can be achieved. Platform: |
Size: 380928 |
Author:qichao |
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Description: In this project ,we propose a color based segmentation method that uses the c means clustering technique to track tumor objects in magnetic resonance (MR) brain images. The key concept in this color based segmentation algorithm with k means means to convert a given gray level MR image in to a color space image and then separate the position of tumor objects from other items of an MR image by using c means clustering
And histogram clustering .Experiments demonstrates that the method can successfully achieve segmentation for MR brain images to help pathologists distinguish exactly lesion size and region.
-In this project ,we propose a color based segmentation method that uses the c means clustering technique to track tumor objects in magnetic resonance (MR) brain images. The key concept in this color based segmentation algorithm with k means means to convert a given gray level MR image in to a color space image and then separate the position of tumor objects from other items of an MR image by using c means clustering
And histogram clustering .Experiments demonstrates that the method can successfully achieve segmentation for MR brain images to help pathologists distinguish exactly lesion size and region.
Platform: |
Size: 2048 |
Author:pramod |
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Description: 用matlab编程工具，编写具有操作界面的应用程序，通过菜单、对话框，选项框等界面控制，对算法进行演示。需要在应用系统中实现的算法及功能包括：
1、图像增强算法
（1）灰度线形变换：亮度及对比度可以调节（通过控制参数的改变，能够实时预览变化结果）；
（2）直方图均衡：可在界面上对比均衡前后的效果。
2、图像变换算法
（3）对一幅彩色图像进行DCT变换和反变换，对比结果和原图；
（4）仅保留左上角16X16的DCT系数，进行反变换，计算结果图的信噪比SNR。
3、图像分割算法
（5）采用最优阈值算法对灰度图像进行分割；
（6）用Canny算法对灰度图像进行边缘检测；
（7）用hough变换，检测边缘图像中的直线，并用不同颜色将检测出的直线叠加显示到原图像上。
-Preparation of a user interface with Matlab programming tools, applications, menus, dialog boxes, option boxes and other interface control, the algorithm demo. Algorithms and functions that need to be achieved in the application system including: 1, the image enhancement algorithm (1) gray linear transformation: the brightness and contrast can be adjusted (by controlling the change of the parameters, it is possible to real-time preview changes result) (2) Histogram equalization : contrast before and after equalization effect in the interface. 2, an image transformation algorithm (3) for a color image DCT transform and inverse transform, comparing the results and the original (4) to retain only the upper left corner of 16x16 DCT coefficient, the inverse transform, the signal-to-noise ratio SNR calculation results of FIG. . 3, image segmentation algorithm (5) The optimal threshold algorithm to gray-scale image segmentation (6) Canny algorithm for edge detection of gray-scale images ( Platform: |
Size: 822272 |
Author:张涛 |
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Search - histogram for color image by matlab