Description: 这是一个基于颜色特征的图像检索系统，是我下了好多之后发现的最好的一个，可以做为毕业设计的，很好的，快下吧！-This is a color feature based image retrieval system is under a lot after I found the best one can be designed as a graduation, a good, fast, are you! Platform: |
Size: 9484288 |
Author:灿灿 |
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Description: 开始检索”调用DoBrowse--- 功能：用于管理ListBox(1)首先取出处理的起始目录路径
(2)调用SiapCariRecursive来对目录中各文件进行处理,这里面又分好几层关系。
（a）锁定一些暂时不用的按键，使在检索处理过程中，不让用户操作，乱按。
（b）调用CariRecursive函数：功能是分别提取目录中各个文件，并进行计算颜色直方图。这个函数又分下面几层：
(i)循环递归调用CariRecursive，找到所选目录下是否有子目录，有子目录进入子目录先处理
(ii)调用ScanFile，提取子目录中的一个个文件。
(iii)上面一步中，每找到一个文件，就调用Madhosi，进行计算颜色直方图（这部分与第1大点中，对关键图处理过程一样），并与关键图的颜色直方图比较，得到相似度，最后在把相似度保存到ListBox中去，同时对应填入对应的文件路径。
(iv)循环至(i)直到目录中所有文件都处理过，才结束CauRecursive,退出该函数。
(3)根据ListBox里面的内容，调整ListBox的宽度。按相似度距离，按从小到大把各文件排列在ListBox中。-Due to the development of multimedia technology and fast expanding of visual information, an effective method is sharply needed to manage and retrieve visual information. So, the Content Based Image and Video Retrieval technology comes into being and become an important research area in multimedia retrieval and image processing.
This thesis focuses on the application of Content based image retrieval (CBIR) technology in defense information technology area. The research on this topic is of great significance in theory and practice. The main work of this thesis lies on:
This thesis makes extensive and deep research in CBIR technology. The status quo and key technologies are introduced, the bottle-neck and development trend are also discussed. The thesis analyzes the application requirement for CBIR technology in defense IT area, and proposes a reasonable application model. The experimental results show that the method is reasonably better than existing methods.
Keywords: content-base Platform: |
Size: 5671936 |
Author:李明福 |
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Description: 详细设计了基于颜色直方图的图像检索 效果不错 计算速度快-Detailed design of the color histogram-based image retrieval good results fast calculation Platform: |
Size: 1024 |
Author:jiashijie |
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Description: OpenGL编程指南第六版 ,英文电子书pdf格式-he OpenGL? Programming Guide, Sixth Edition, provides definitive and comprehensive information on OpenGL and the OpenGL Utility Library. The previous edition covered OpenGL through Version 2.0. This sixth edition of the best-selling "red book" describes the latest features of OpenGL Version 2.1. You will find clear explanations of OpenGL functionality and many basic computer graphics techniques, such as building and rendering 3D models interactively viewing objects from different perspective points and using shading, lighting, and texturing effects for greater realism. In addition, this book provides in-depth coverage of advanced techniques, including texture mapping, antialiasing, fog and atmospheric effects, NURBS, image processing, and more. The text also explores other key topics such as enhancing performance, OpenGL extensions, and cross-platform techniques.
Using server-side pixel buffer objects for fast pixel rectangle download and retrieval
Discussion of the sRGB texture f Platform: |
Size: 15385600 |
Author:陆天华 |
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Description: 使用OpenCV做的一个人脸检索系统，包括实现了静态图片的人脸检测，以及视频流中的人脸检测，和人脸匹配，实现了视屏播放，在视频中快速检索需要寻找的人脸目标-Using OpenCV to do a face retrieval system, including the realization of the static image of face detection and video streaming in face detection and face matching, to achieve the Screen Play, fast retrieval in the video need to find the human face target Platform: |
Size: 5933056 |
Author:赵宾 |
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Description: Matlab+图形图像处理函数详细列表,包含常用函数列表，快速检索-Matlab+ Graphics detailed list of image processing functions, including a list of common functions, fast retrieval Platform: |
Size: 427008 |
Author:皮皮 |
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Description: Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult tasks in digital image processing. Detection of salient image regions is useful for applications like image segmentation, adaptive compression, and region-based image retrieval. This problem can be tackled by mapping the pixels into various feature spaces, which are subjected to various grouping algorithms It present a novel method to determine salient regions in images using low-level features of luminance and color. The method is fast, easy to implement and generates high quality saliency maps of the same size and resolution as the input image. Platform: |
Size: 560128 |
Author:shailesh kochra |
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Description: Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult tasks in digital image processing. Detection of salient image regions is useful for applications like image segmentation, adaptive compression, and region-based image retrieval. This problem can be tackled by mapping the pixels into various feature spaces, which are subjected to various grouping algorithms It present a novel method to determine salient regions in images using low-level features of luminance and color. The method is fast, easy to implement and generates high quality saliency maps of the same size and resolution as the input image. Platform: |
Size: 1024 |
Author:shailesh kochra |
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Description: Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult tasks in digital image processing. Detection of salient image regions is useful for applications like image segmentation, adaptive compression, and region-based image retrieval. This problem can be tackled by mapping the pixels into various feature spaces, which are subjected to various grouping algorithms It present a novel method to determine salient regions in images using low-level features of luminance and color. The method is fast, easy to implement and generates high quality saliency maps of the same size and resolution as the input image. Platform: |
Size: 1024 |
Author:shailesh kochra |
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Description: Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult tasks in digital image processing. Detection of salient image regions is useful for applications like image segmentation, adaptive compression, and region-based image retrieval. This problem can be tackled by mapping the pixels into various feature spaces, which are subjected to various grouping algorithms It present a novel method to determine salient regions in images using low-level features of luminance and color. The method is fast, easy to implement and generates high quality saliency maps of the same size and resolution as the input image. Platform: |
Size: 1024 |
Author:shailesh kochra |
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Description: Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult tasks in digital image processing. Detection of salient image regions is useful for applications like image segmentation, adaptive compression, and region-based image retrieval. This problem can be tackled by mapping the pixels into various feature spaces, which are subjected to various grouping algorithms It present a novel method to determine salient regions in images using low-level features of luminance and color. The method is fast, easy to implement and generates high quality saliency maps of the same size and resolution as the input image. Platform: |
Size: 1024 |
Author:shailesh kochra |
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Description: Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult tasks in digital image processing. Detection of salient image regions is useful for applications like image segmentation, adaptive compression, and region-based image retrieval. This problem can be tackled by mapping the pixels into various feature spaces, which are subjected to various grouping algorithms It present a novel method to determine salient regions in images using low-level features of luminance and color. The method is fast, easy to implement and generates high quality saliency maps of the same size and resolution as the input image. Platform: |
Size: 1024 |
Author:shailesh kochra |
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Description: Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult tasks in digital image processing. Detection of salient image regions is useful for applications like image segmentation, adaptive compression, and region-based image retrieval. This problem can be tackled by mapping the pixels into various feature spaces, which are subjected to various grouping algorithms It present a novel method to determine salient regions in images using low-level features of luminance and color. The method is fast, easy to implement and generates high quality saliency maps of the same size and resolution as the input image. Platform: |
Size: 1024 |
Author:shailesh kochra |
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Description: Image segmentation systems have the potential to dramatically improve the performance of Digital image processing. Segmentation procedures partition an image into its constituent parts or objects. In general, segmentation is one of the most difficult tasks in digital image processing. Detection of salient image regions is useful for applications like image segmentation, adaptive compression, and region-based image retrieval. This problem can be tackled by mapping the pixels into various feature spaces, which are subjected to various grouping algorithms It present a novel method to determine salient regions in images using low-level features of luminance and color. The method is fast, easy to implement and generates high quality saliency maps of the same size and resolution as the input image. Platform: |
Size: 1024 |
Author:shailesh kochra |
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Description: 基于视觉单词树的快速图像检索，fast iamge retrieval through vocabulary tree.-Based on visual word tree fast image retrieval, fast iamge retrieval through vocabulary tree. Platform: |
Size: 558080 |
Author:wangyilin |
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Description: 对于以图片为主的应用来说（比如Path），传统的从硬盘单个加载图片方法太慢以致于会影响到应用的整体性能表现，尤其是需要滚动加载的。Fast Image Cache刚好可以解决这个问题。Fast Image Cache是iOS 应用中一个高效的，快速的图片存储和检索方法。对于很多优秀的应用来说，快速运行和平缓滚动是用户体验中重要的一部分，而Fast Image Cache可以简单化这种实现-For a picture-based applications (such as Path), the traditional method of load images from a single hard disk too slow to affect the overall performance of the application, in particular the need to scroll loaded. Fast Image Cache just to solve this problem. Fast Image Cache iOS application is an efficient, fast image storage and retrieval methods. For many excellent applications, running fast and smooth scrolling is an important part of the user experience, while Fast Image Cache can simplify this implementation Platform: |
Size: 1736704 |
Author:anxianjie |
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Description: 基于内容的图像检索技术，利用颜色特征提取，检索准确速度快-Content-based image retrieval techniques, the use of color feature extraction, fast and accurate retrieval Platform: |
Size: 1024 |
Author: |
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Description: 基于深度学习框架构建用于快速图像检索的二值哈希编码(Construction of binary hash codes for fast image retrieval based on depth learning framework) Platform: |
Size: 7405568 |
Author:cumtstrive
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Search - fast image retrieval