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CBIR
- 本程序实现了基于内容的图像检索功能,也就是说如何根据图像的内容从多媒体数据库中索引或发现匹配的图像,所用的方法是傅立叶变换,小波变换等技术.-the program content-based image retrieval functions, in other words how images from the multimedia database indexing or find matching images, the methodology used is the Fourier t
CBIR
- A paper that I presented on Supervisory Control and Data Acquisition (SCADA) won the second prize at the symposium conducted by the Electrical and Electronics Engineering department of the SRM University. Other topics on which I presented papers were
josTexImgRetr
- 基于纹理谱描述子的图像检索 提出一种新的纹理谱描述子应用于基于内容的图像检索中.讨论了小波变换的思想和纹理谱概念的联 系,根据纹理的视觉特性,提出纹理模式等价类的概念,设计出更合理的纹理谱描述子来描述图像的纹理特征.该纹 理模式刻画了领域内像素灰度变化模式,以纹理谱直方图方式表示图像纹理内容.分析了纹理谱的对称不变性和旋 -This paper presents a new texture spectrum descr iptor for content-based image
invmoments
- calculate seven hu moment for image recognition and CBIR
CBIR
- This project focuses on calculating the similarity between the images using genetic algorithm and haar-wavelet. Haar wavelet is being used in order to calculate the images with different features like various expressions or gloomy or other characteri
Scalable-Indexing-Schemes-of-Color-Image-Archives
- Background of Content Based Image Retrieval(CBIR) Analysis of Previous Work Results of Existing Methods Scalable Image Indexing and Retrieval Proposed Indexing System(overview) wavelet transform and HSL color conversion Feature Space(Ener
Wavelet-CBIR
- Content based image retrieval CBIR
colourhistogram
- Colourhistogram II. TEXTURE FEATURE EXTRACTION IN CBIR An overview of the proposed CBIR system is illustrated in Fig. 1. The proposed algorithm, Label Wavelet Transform (LWT), is based on color image segmentation [1], and it is an extens
CBIR
- Content based image retrieval in java using k-means clustering and haar wavelet transform
CBIR-system
- 随着计算机科技的发展，图像检索的应用也越来越成熟，根据检索性质可分为两类：基于文本的图像检索和基于内容的图像检索。本论文通过研究基于内容的图像检索中的几个核心算法，用于聚类分析的K-means算法，通过haar小波变换来提取图像底层视觉特征，以及使用F-范数理论来进行相似性度量，来设计一个离线的图像检索系统。(With the development of computer technology, the application of image retrieval is more and mo