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As the local contrast of retinal blood vessel is unstable, especially in unhealthy fundus images, an open active contour based method is presented for automated segmentation of retinal vessels. Firstly, we proposed a new initial parameters giving method and a pair of correlation open active contour model, based on these method, each vessel edge is modeled with an active contour which initiated by...
Detecting the spatial objects is an important research agenda for geospatial information science. Appling object-oriented image classification to extract GIS features, which fulfills the needs of updating the geospatial databases with remote sensing imagery will greatly enhance the ongoing digital city construction and national condition monitoring. This paper describes the key technology for high...
Image class segmentation is a problem that combines image segmentation and image classification. Conditional random field can be used in image class segmentation to achieve state-of-the-art result, adding high-level information in the course of using low-level cues to conduct segmentation. In this paper we introduce a method using weighted neighborhood histogram on the over-segmented original images...
In this paper, the problem of foreground segmentation in videos is considered. The bag of superpixels is proposed to simultaneously model both the foreground and the background. Then it is demonstrated that an image has a hierarchical structure. Based on this observation, the discriminative nature of sparse representations is exploited to segment the foreground in each frame. Experimental results...
Segmentation is a fundamental issue in synthetic aperture radar (SAR) image analysis. When contrast results against the true landscape, multi-polarization SAR images can provide more information, and obtain more correct segmentation than only single polarization SAR image. This paper presented a new SAR image segmentation method based on the multi-polarization SAR images fusion. The method built the...
A fast and effective fade detection algorithm is proposed in this paper, which directly operates in compressed domain and suitable for real-time implementation. By analyzing the prediction directions of B frames, which are revealed in the macroblock types, the candidate fades can be found. Then, uncommon intracoded macroblocks of the P frame can be applied as an indicator of fade. As a result, locating...
A self-enhanced SVM (support vector machines) building detection scheme is discussed. The scheme was designed for 1-metre resolution satellite imagery analysis. The scheme is a learning based segmentation without any prior prepared training data set. In the initial stage, an adaptive two-dimension Otsu algorithm is adopted to segment the image primarily into buildings and non-buildings. Then the segmented...
An adaptive method is presented in this paper to cope with Gaussian noise through local structure estimation. Even regions and uneven regions are distinguished firstly, then each uneven region is further segmented into two subregions by fuzzy c-means clustering algorithm and Fisher discriminant analysis. Finally, linear approximation is used to estimate the intensities of each region. With the introduction...
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