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Image Segmentation Using an Improved watershed algorithm

Journal of Shanghai Jiaotong university(Science) 2004年第2期9卷 16-19页

作者：郭礼华李建华杨树堂陆松年 School of Electronic & Information Technology

As watershed algorithm suffers from over-segmentation problem, this paper presented an efficient method to resolve this problem. First, pre-process of the image using median filter is made to reduce the effect of noise. Second, watershed algorithm is employed to provide initial regions. Third, regions are merged according to the information between the region and boundary. In the merger processing based on the region information, an adaptive threshold of the difference between the neighboring regions is used as the region merge criteria, which is based on the human visual character. In the merger processing on the boundary information, the gradient is used to judge the true boundary of the image to avoid merging the foreground with the background regions. Finally, post-process to the regions using mathematical morphology open and close filter is done to smooth object boundaries. The experimental results show that this method is very efficient.

关键词： image segmentation region merger watershed algorithm

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Wavelet-based watershed for image segmentation algorithm

Wavelet-based watershed for image segmentation algorithm

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6th World Congress on Intelligent Control and Automation

作者： Chai, Yu-hua Gao, Li-qun Lu, Shun Tian, Lei Northeastern Univ Inst Informat Sci & Engn Shenyang 110004 Liaoning Prov Peoples R China Semicond Mfg Int Corp Beijing 100176 Peoples R China

ISBN: (纸本)1424403316

A watershed image segmentation method based on wavelet transform is proposed. Firstly, source image was filtered by multi-scale morphological filtering and the filtered image was decomposed by wavelet, then the low-frequency approximate image was segmented into many small regions by watershed algorithm and these regions were merged according to some region mergence rules to get the original segmentation image. Finally, the original segmentation image was projected into a full-resolution image by inverse-wavelet transform to get the final segmentation image. Utilizing multi-scale morphological filtering and the multi-resolution characteristic of wavelet transform, this method solves effectively the problems of sensitizing to noises and over-segmentation phenomenon of watershed algorithm, and the computing speed is improved.

关键词： wavelet transform image segmentation watershed algorithm morphological gradient reconstruction

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An efficient and robust algorithm for 3D mesh segmentation

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MULTIMEDIA TOOLS AND APPLICATIONS 2006年第2期29卷 109-125页

作者： Chen, Lijun Georganas, Nicolas D. Univ Ottawa Sch Informat Technol & Engn Ottawa ON K1N 6N5 Canada

This paper presents an efficient and robust algorithm for 3D mesh segmentation. Segmentation is one of the main areas of 3D object modeling. Most segmentation methods decompose 3D objects into parts based on curvature analysis. Most of the existing curvature estimation algorithms are computationally costly. The proposed algorithm extracts features using Gaussian curvature and concaveness estimation to partition a 3D model into meaningful parts. More importantly, this algorithm can process highly detailed objects using an eXtended Multi-Ring (XMR) neighborhood based feature extraction. After feature extraction, we also developed a fast marching watershed-based segmentation algorithm followed by an efficient region merging scheme. Experimental results show that this segmentation algorithm is efficient and robust.

关键词： 3D mesh Gaussian curvature concaveness XMR neighborhood watershed algorithm region merging

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A new segmentation method of CR images based on discrete wavelet transform and mathematics morphology

A new segmentation method of CR images based on discrete wav...

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20th Congress of the International-Commission-for-Optics

作者： Li, Z Huang, LQ Chinese Acad Sci Changchun Inst Opt Fine Mech & Phys Changchun 130022 Peoples R China Chinese Acad Sci Grad Sch Beijing Peoples R China

ISBN: (纸本)0819460583

In this paper, we propose a segmentation method of CR(computed radiography) images with being rid of under-segmentation and over-segmentation. An under-segmentation occurs when pixels belonging to different objects are grouped into a single region. Such errors are the most dangerous because they can invalidate the whole segmentation process. The phenomenon always takes place when we segment CR images because of the principle of CR. In order to depressed under-segmentation, we enhance the CR images using DWT (discrete wavelet transform) to get more detail of CR image features. As we enhance the CR image, the over-segmentation maybe occurs. Compared with under-segmentation, the over-segmentation occurs when a single objects is subdivided by segmentation into several region. For the purpose of preventing from the over-segmentation, we present a scheme for enhanced CR images based on watershed algorithm that solves over-segmentation problem. We use marker-based watershed algorithm. Together with gradient image and marker image, watershed segmentation can make sure to partition CR image into meaningful object and avoid further segmentation of homogeneous regions. The result of the proposed algorithm are compared with those of other standard methods. Experiments have shown a better result and indeed solved under-segmentation and over-segmentation problems.

关键词： watershed algorithm under-segmentation discrete wavelet transform CR image over-segmentation

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A MMW radiometric imaging partition method based on the morphology algorithm

A MMW radiometric imaging partition method based on the morp...

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Joint 31st International Conference on Infrared and Millimeter Waves/14th International Conference on Terahertz Electronics

作者： Zhang, Guangfeng Li, Xingguo Nanjing Univ Sci & Technol Inst Millimeter Wave & Light Wave Near Sensing T Nanjing 210094 Peoples R China

ISBN: (纸本)9781424403998

Because of working at all day and all weather, a MMW radiometer can provide more specific information than infrared and optical detectors. But it is urgent to solve the important problem of the MMW radiometric image partition of multiple targets for target identification. By confirming the different brightness area of radiometric image based on MMW radiation characteristic, a new approach to radiometric image partition is presented based on the morphology pretreatment and image partition of watershed algorithm. The partition result of 3mm band radiometric image shows the algorithm is virtual partition for low brightness temperature targets.

关键词： Brightness temperature Image partition Radiometric image Target recognition watershed algorithm

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A multichannel watershed-based algorithm for supervised texture segmentation

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PATTERN RECOGNITION LETTERS 2003年第9-10期24卷 1545-1554页

作者： Malpica, N Ortuño, JE Santos, A Univ Politecn Madrid Dept Ingn Elect E-28040 Madrid Spain

Segmentation of image regions based on their texture is a standard problem in image analysis. Once a set of texture features is selected, several algorithms can be applied to segment the image into regions. This paper presents an extension of the watershed algorithm using a vector gradient and multivariate region merging methods. The algorithm uses a set of texture images, and it only depends on an adjustable parameter. Results are presented on a standard set of synthetic images and on textured medical ones, using different texture parameters and merging criteria. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： texture segmentation watershed algorithm multichannel information

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Automatic extraction of video object plane by integrating space-time information

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Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics 2006年第6期18卷 865-869页

作者： Yang, Wenming Liu, Jilin Wang, Qicong Department of Information Science and Electronic Engineering Zhejiang University Hangzhou 310027 China

An automatic video object plane extraction algorithm is proposed. At first, a binary moving mask is obtained by Gaussian test based on temporal motion information, followed by a further test by establishing MRF model on double-scale neighborhood to achieve smooth and complete binary moving mask. Then, an improved watershed algorithm based on nonlinear transform is employed to segment moving regions. Finally, moving objects are extracted by performing ratio operation on spatial and temporal results. Experimental results validate the proposed algorithm.

关键词： Double-scale neighborhood Gaussian test MRF model Ratio operation Video object plane watershed algorithm

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An improved algorithm for shot cut detection

An improved algorithm for shot cut detection

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Conference on Visual Communications and Image Processing 2005

作者： Hashimah, PN Gao, L Qahwaji, R Jiang, JM EIMC Dept Bradford W Yorkshire England

ISBN: (纸本)0819459763

The increasing availability and use of online video has led to a high demand for very accurate and efficient automated video analysis techniques. Previous research has concentrated on segmenting videos by detecting the boundaries between camera shots. Shot cut detection is the first step in every video indexing and retrieval algorithm. A number of automated shot-change detection methods for indexing a video sequence to facilitate browsing and retrieval have been proposed in recent years. However, there is no dataset that is internationally agreed upon to be used as a benchmark for evaluating the emerging techniques. In this paper, a new algorithm is proposed for the shot cut detection. The detection algorithm consists of three major stages. The morphological Hit-Miss transform is applied in the first stage. The watershed transform is applied next and finally feature extraction is carried out. To enable comparison with previous work, the dataset used in this new algorithm is applied to the technique introduced by T. Y. Liu et al.,2004. Our algorithm shows a remarkable difference and it provides a better recall and precision rates.

关键词： watershed algorithm shot cut detection Hit-Miss Transform MPEG video sequence

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Development of a watershed algorithm for multi-resolution, multi-dimensional clustering of hyperspectral data

Development of a watershed algorithm for multi-resolution, m...

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Conference on algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII

作者： Jellison, GP Hemmer, TH Wilson, DG SITAC Fairfax VA 22033 USA

ISBN: (纸本)0819444758

The watershed-clustering algorithm was adapted for use in multi-dimensional spectral space and was used to define clusters in Hyperspectral Digital Imagery Collection Experiment (HYDICE) data. This algorithm identifies clusters as peaks in a B-dimensional topographic relief, where B is the number of wavelength bands. Image pixel spectra are represented as points in this multi-dimensional space. Analysis is done at increasing values of radiometric resolution, defined by the number of segments into which each wavelength axis is divided. Segmentation of the axes divides the multi-dimensional space into bins, and the number of pixels in each bin is determined. The histogram of the bin populations defines the topography for the watershed analysis. Spectral clusters correspond to mountains or islands on this multi-dimensional surface. The algorithm is analogous to submerging this topography under water, and revealing clusters by determining when mountain peaks appear as the water surface is lowered. Testing of this algorithm reveals some surprising features. Although increasing the radiometric resolution (bins per axis) generally results in large clusters breaking up into greater numbers of small clusters, this is not always the case. Under some circumstances, the separate clusters can recombine into one large cluster when radiometric resolution is increased. This behavior is caused by the existence of single-pixel voxels, which smoothes out the topography, and by the fact that the voxels retain a surprising degree of connectivity, even at high radiometric resolutions. These characteristics of the high-dimensional spectral data provide the basis for further development of the watershed algorithm.

关键词： hyperspectral unsupervised clustering watershed algorithm multi-resolution automated end-member selection HYDICE

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Application of multiresolution, multidimensional clustering of hyperspectral data using the watershed algorithm

Application of multiresolution, multidimensional clustering ...

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Conference on algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII

作者： Hemmer, TH Jellison, GP Wilson, DG SITAC Fairfax VA 22033 USA

ISBN: (纸本)0819444758

In many applications of remotely-sensed imagery, one of the first steps is partitioning the image into a tractable number of regions. In spectral remote sensing, the goal is often to find regions that are spectrally similar within the region but spectrally distinct from other regions. There is often no requirement that these regions be spatially connected. Two goals of this study are to partition a hyperspectral image into groups of spectrally distinct materials, and to partition without human intervention. To this end, this study investigates the use of multi-resolution, multi-dimensional variants of the watershed-clustering algorithm on Hyperspectral Digital Imagery Collection Experiment (HYDICE) data. The watershed algorithm looks for clusters in a histogram: a B-dimensional surface, where B is the number of bands used (up to 210 for HYDICE). The algorithm is applied to HYDICE data of the Purdue Agronomy Farm, for which "ground truth" is available. watershed results are compared to those obtained by using the commonly-available Iterative Self-Organizing Data Analysis Technique (ISODATA) algorithm.

关键词： hyperspectral unsupervised clustering watershed algorithm multi-resolution automated end-member selection HYDICE

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