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[Wavelet] 50 DL : 0: 多媒体技术的发展和视觉信息的飞速膨胀迫切需要对视觉信息资源的有效管理和检索。由此，基于内容的图像和视频检索技术得到了越来越多的重视，成为了多媒体信息检索和图像处理领域中的重要研究方向。CBIR技术将对大规模图像信息的管理和访问提供有力支持。本文这种介绍了内容图像检索的灰度特征实现方法，具有理论意义和实际应用价值。针对基于内容图像检索技术进行了研究，介绍了其研究现状和关键技术，讨论了其技术瓶颈和发展趋势。共生矩阵法，是对图像的所有像元进行统计调查，以便描述其灰度分布的一种方法。分析了这种基于广义图像灰度共生矩阵的图像检索方法，该方法首先将原图像作平滑处理得到平滑图像，然后将原图像和平滑图像组合得到广义图像灰度共生矩阵，提取该矩阵的统计特征量，最后将该统计量组成归一化向量用以检索。实验结果表明，本方法的效果要优于单纯的灰度共生矩阵法。在对相似图像检索时，该算法与基于共生矩阵的经典算法相当，在面临同一图像大小显著改变或发生旋转的情况下，该算法明显优于经典算法。相比较而言，该算法提高了检索的有效性。 -The development of multimedia technology and the expansion of visual information，which cries for the effective management and retrieval methods of visual information. Thus, the image and video searching technology based on content is gaining more and more attention to become a multimedia information retrieval and image processing in the field of important research direction. The technology of CBIR provides effective supports for the management and access of extensive image information. This paper introduced the content of the image retrieval method characteristics of gray, with theoretical and practical value. This paper does an extensive and in-depth study of technology based on content image retrieval to, presenting their research status and key technologies, discussing its development trends and technological bottlenecks. Co-occurrence matrix of all the pixel image survey has been conducted in order to describe a method of distribution of gray. This paper analyses this broad-based
Date : 2025-12-24 Size : 557kb User : qichao
[Wavelet] wavelet-and-its-application DL : 0: 小波技术及其应用的一个PDF文档，非常好地介绍了小波的历史、发展、以及应用现状。适合初接触小波的人学习。-Wavelet technology a PDF document and its applications, very good introduction to the history of the wavelet, development, and application status. For people to learn early contact with wavelets.
Date : 2025-12-24 Size : 84kb User : 万相奎
[Wavelet] 3900001 DL : 0: 本文研究的是利用奇异性指数实现对设备状态监视和故障预警功能。首先用LabVIEW 采集传感器电信号，然后对采集到的电信号进行小波变换得到信号包络奇异点的奇异性指数，即设备运行状态的特征值-In this research project, we use LabVIEW to do wavelet-transformation to the signal collected by sensors in order to get singularity index from the singular points of the particular signal’s envelope. Through comparing this eigenvalue to the figures in a standard database, we can know the functional status of the instruments. Not only the diagnoses are continuously displayed, but alarms about signs of dysfunction will also be raised in a proper way. In other words, both the supervision of the instrument and warning of dysfunction can be achieved
Date : 2025-12-24 Size : 158kb User : whb