Mr. Hongsheng Zhang Profile

Hongsheng Zhang

at South China Normal Univ

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Publications (2)

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Proceedings Article | 29 December 2008 Paper

Shape-adaptive neighborhood classification method for remote sensing image

Hongsheng Zhang, Yan Li

Proceedings Volume 7285, 72850F (2008) https://doi.org/10.1117/12.815857

KEYWORDS: Remote sensing, Feature extraction, Image classification, Image segmentation, Image processing, Spatial resolution, Shape analysis, Analytical research, RGB color model, Image fusion

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High spatial resolution remote sensing images are playing an increasing important role in various applications in the world. As the fundamental work, classification of remote sensing is significant in the applications. This paper proposed a new feature extraction approach based on the shape adaptive neighborhood (SAN) for the classification of high spatial resolution remote sensing images. The heterogeneity based on the color characteristics was employed to determine the SAN of each pixel. Then all the color features, texture features and shape features were extracted from each SAN, and were fused by the feature level data fusion methods to the final feature space of the RS image. Then the features were used to do the classification work. As the experiment results shown, the total precision of the classification was 0.9187, and the kappa coefficient was 0.7950. By analyzing different maximum size of the SAN and different threshold of the heterogeneity, the best maximum size of the SAN was 11*11 for the study area and the most suitable threshold was 0.5.

Proceedings Article | 11 November 2008 Paper

Toward a 2D vector map with a feature nodes-based watermarking method

Hongsheng Zhang, Yan Li

Proceedings Volume 7146, 71461P (2008) https://doi.org/10.1117/12.813153

KEYWORDS: Digital watermarking, Geographic information systems, Information security, Lithium, Visualization, Data modeling, Raster graphics, 3D modeling, Wavelets, Binary data

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With a wide use of vector maps, the copyright issue is educing an increasing importance and attracting focus on the transmission and the exchange of the vector maps through a network environment. This paper discusses a feature nodes based watermarking method (FNBW) towards keeping robustness and high accuracy of digital map based on SVG and GML format. The digital map treats as a set of curves in the embedding algorithm, and each curve was divided up into several shorter curves under two given thresholds. And then a watermark bit combined with user certificate was embedded into each segment around the feature nodes with the maximum curvature in the segment series nodes. To extract the watermark, all watermark nodes were calculated and searched for in the watermarked map with the Watermark node Searching Algorithm by using the original map. Finally the method calculates the similarity between the original watermark bits and the extracted ones, and determines whether the watermark exists or not. As the experiment result shown, the method not only guarantees the accuracy of vector map but also possesses the good robustness, such as it gives 1.00 similarity under no attack or only geometric transformation with the map; And the anticopping ability is also good enough to give a more than 0.87 similarity for the map cropped 80%. In addition, the method has the full ability of anti-compression lossless methods and good ability to the loss approaches. And an experiment curve of the similarity threshold was given in the paper, which helped to control the anti-attack ability of the watermark and set parameters for an automatic procedure of watermark detection.

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