中国科学院机构知识库网格系统: 检索

Orthogonal sparse fractal coding algorithm based on image texture feature 期刊论文 OAI收割
IET IMAGE PROCESSING, 2019, 卷号: 13, 期号: 11, 页码: 1872-1879
作者: Cao, Jian; Zhang, Aihua; Shi, Lei

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收藏 | 浏览/下载：224/0 | 提交时间：2019/10/11

image coding feature extraction fractals data compression image texture image reconstruction orthogonal codes image colour analysis transforms decomposition matrix algebra orthogonal sparse grey level sparse decomposition decoding speed orthogonal sparse fractal coding algorithm image reconstruction quality image texture feature extraction fractal image compression coding algorithm grey description feature extraction orthogonal sparse grey level transform

Texture Classification in Extreme Scale Variations Using GANet 期刊论文 OAI收割
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2019, 卷号: 28, 期号: 8, 页码: 3910-3922
作者: Chen, Xilin; Liu, Li; Chen, Jie; Zhao, Guoying; Fieguth, Paul

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收藏 | 浏览/下载：61/0 | 提交时间：2019/08/16

Texture descriptors rotation invariance local binary pattern (LBP) feature extraction texture analysis

Feature-aware natural texture synthesis 期刊论文 OAI收割
The Visual Computer, 2014, 卷号: 2016, 期号: 32, 页码: 43-55
作者: Wu, Fuzhang; Dong, Weiming; Kong, Yan; Mei, Xing; Yan, Dong-Ming

收藏 | 浏览/下载：28/0 | 提交时间：2016/04/13

texture synthesis texture feature analysis composite texture feature-aware synthesis

TextureGrow: Object recognition and segmentation with limit prior knowledge (EI CONFERENCE) 会议论文 OAI收割
2011 International Conference on Network Computing and Information Security, NCIS 2011, May 14, 2011 - May 15, 2011, Guilin, Guangxi, China
Yao Z.; Han Q.

收藏 | 浏览/下载：24/0 | 提交时间：2013/03/25

In this paper we present a new method for automatically visual recognition and semantic segmentation of photographs. Our automatically and rapidly approach based on Cellular Automation. Most of the analysis and description of recognition and segmentation are based on statistical or structural properties of this attribute most of them need plenty of samples and prior Knowledge. In this paper within a few evident samples (not too many) we can first get the texture feature of each component and the structures then select the approximately location randomly of the objects or patches of them then we use the Cellular Automata algorithm to "grow" based on texture of different objects. The grow progress will stop When texture grow to the boundary. By this steps a new method is found which allow us use very few samples and low lever experience and get a rapidly and accuracy way to recognize and segment objects. We found that this new propose gives competitive results with limited experience and samples. 2011 IEEE.

Research on infrared dim-point target detection and tracking under sea-sky-line complex background (EI CONFERENCE) 会议论文 OAI收割
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China
作者: Dong Y.-X.; Zhang H.-B.; Li Y.; Li Y.; Li Y.

收藏 | 浏览/下载：108/0 | 提交时间：2013/03/25

Target detection and tracking technology in infrared image is an important part of modern military defense system. Infrared dim-point targets detection and recognition under complex background is a difficulty and important strategic value and challenging research topic. The main objects that carrier-borne infrared vigilance system detected are sea-skimming aircrafts and missiles. Due to the characteristics of wide field of view of vigilance system the target is usually under the sea clutter. Detection and recognition of the target will be taken great difficulties.There are some traditional point target detection algorithms such as adaptive background prediction detecting method. When background has dispersion-decreasing structure the traditional target detection algorithms would be more useful. But when the background has large gray gradient such as sea-sky-line sea waves etc.The bigger false-alarm rate will be taken in these local area.It could not obtain satisfactory results. Because dim-point target itself does not have obvious geometry or texture feature in our opinion from the perspective of mathematics the detection of dim-point targets in image is about singular function analysis.And from the perspective image processing analysis the judgment of isolated singularity in the image is key problem. The foregoing points for dim-point targets detection its essence is a separation of target and background of different singularity characteristics.The image from infrared sensor usually accompanied by different kinds of noise. These external noises could be caused by the complicated background or from the sensor itself. The noise might affect target detection and tracking. Therefore the purpose of the image preprocessing is to reduce the effects from noise also to raise the SNR of image and to increase the contrast of target and background. According to the low sea-skimming infrared flying small target characteristics the median filter is used to eliminate noise improve signal-to-noise ratio then the multi-point multi-storey vertical Sobel algorithm will be used to detect the sea-sky-line so that we can segment sea and sky in the image. Finally using centroid tracking method to capture and trace target. This method has been successfully used to trace target under the sea-sky complex background. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

An integrated aurora image retrieval system: AuroraEye 期刊论文 OAI收割
journal of visual communication and image representation, 2010, 卷号: 21, 期号: 8, 页码: 787-797
作者: Fu, Rong; Gao, Xinbo; Li, Xuelong; Tao, Dacheng; Jian, Yongjun

收藏 | 浏览/下载：220/61 | 提交时间：2011/01/11

Content-based image retrieval Aurora Adaptive LBP Gabor Image texture analysis Database Feature extraction Local binary pattern

Object-oriented Change Detection Method Based on Multi-scale and Multi-Feature Fusion 会议论文 OAI收割
2009 Joint Urban Remote Sensing Event, Vols 1-3, New York
Wang, Wen-jie; Zhao, Zhong-ming; Zhu, Hai-qing

收藏 | 浏览/下载：32/0 | 提交时间：2014/12/07

Object-oriented multi-scale segment spectral feature texture feature shape feature fusion CHANGE-VECTOR ANALYSIS COVER

Object-oriented Multi-feature Fusion Change Detection Method for High Resolution Remote Sensing Image 会议论文 OAI收割
2009 17th International Conference on Geoinformatics, Vols 1 and 2, New York
Wang, Wen-jie; Zhao, Zhong-ming; Zhu, Hai-qing

收藏 | 浏览/下载：13/0 | 提交时间：2014/12/07

object-oriented segment optimized feature spectral feature texture feature shape feature fusion CHANGE-VECTOR ANALYSIS LAND-COVER CLASSIFICATION

Stochastic video signal's automatic identification and image reproduction (EI CONFERENCE) 会议论文 OAI收割
2007 2nd IEEE Conference on Industrial Electronics and Applications, ICIEA 2007, May 23, 2007 - May 25, 2007, Harbin, China
Mingxiu L.; Guangliang H.

收藏 | 浏览/下载：17/0 | 提交时间：2013/03/25

In order to realize the automatic extraction of stochastic signal's horizontal synchronization frequency and the stable reproduction of video image different image features of horizontal synchronization blanking signal under different deviation are analyzed and spectrum analysis algorithm of horizontal synchronization frequency texture feature extraction algorithm of slope image and phase feature extraction algorithm of drifting image are put forward. Based on the three algorithms the hierarchical automatic recognition algorithm is put forward to automatically control the adjusting of the horizontal synchronization frequency and realize the reproduction. The algorithm was applied in the automatic interception system of computer video leaking information and quick interception and stable reproduction of computer video leaking information were achieved. 2007 IEEE.

医学影像处理与分析中分割方法的研究及应用 学位论文 OAI收割
工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2002
作者: 林瑶

收藏 | 浏览/下载：132/0 | 提交时间：2015/09/02

医学图像处理与分析图像分割模糊连接度纹理特征活动轮廓模型形变模型 Live wire算法 Watershed ACID Medical Image Process and Analysis Image Segmentation Fuzzy Connectedness Texture Feature Active Contour Model Deformable Model