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In this paper we propose a novel algorithm to increase the accuracy of the hippocampus segmentation by using the orientation-scale descriptor(OSD) and the sparse coding. The orientation-scale descriptor are high dimensional features which contains image structure information in difference orientations and scales. The method has four steps. Firstly, extract the orientation-scale descriptors and construct...
Lung segmentation in thoracic computed tomography (CT) scans is an important preprocessing step for computer-aided diagnosis (CAD) of lung diseases. This paper focuses on the segmentation of the lung field in thoracic CT images. Traditional lung segmentation is based on Gray level thresholding techniques, which often requires setting a threshold and is sensitive to image contrasts. In this paper,...
In order to remove the problem of the shadow of moving vehicles in video surveillance, this paper presents an algorithm based on projection features of the connected regions to eliminate the dynamic shadow. Firstly, the Frame Difference method is applied to image blocks to extract the background. Then, the moving vehicles are detected as the foreground in the current frame by background subtraction...
Accurate segmentation of crop leaf lesion is the precondition of precise spraying. A method of lesion segmentation is proposed for image recognition of the precise spraying system in this paper. The method is operated in RGB color space, to separate the normal area and the lesion by intensity change of three color components. The experimental results show that the proposed method achieves a high level...
Shape features are one of the most popular low-level image representations for computer vision (CV) tasks such as template matching, image collaboration and object recognition. In this paper, an application-originated research has been introduced for extracting representative shape characteristics from challenging real-world scenes based on the image “textures”. The proposed new approach starts from...
The systematic evaluation of synthetic aperture radar (SAR) data analysis tools, such as segmentation and classification algorithms for geographic information systems, is difficult given the unavailability of ground-truth data in most cases. Therefore, testing is typically limited to small sets of pseudoground-truth data collected manually by trained experts, or primitive synthetic sets composed of...
In this paper, we present a novel method for human-computer interaction based on finger motion detection. Image processing is used to get the position, motion direction and movement of the marked figure in the video image, and then associate them with the cursor position, motion direction and mouse function using windows underlying functions. Experimental results show that the method can accurately...
In this paper, linking with the basic principle of FCM algorithm, on the basis of theory research, a method of the cluster analysis that FCM and the genetic algorithm are combined together is proposed. Firstly, the approximate optimal solution obtained by the genetic algorithm is taken as the original value of the FCM algorithm, then carrying on the local search to obtain the global optimal solution,...
Aimed at that there is a missing detection in the video shot segmentation because of that the global color feature can't reflect the changes in the image's substance, a new method of shot detection is proposed using global color feature combined with the characteristic of local edge. In order to determine the border of the shot segmentation, the paper eliminated the flash interference with the gray...
In content-based image retrieval, the ldquosemantic gaprdquo between visual image features and user semantics makes it hard to predict abstract image categories from low-level features. We present a hybrid system that integrates global features (G-features) and region features (R-features) for predicting image semantics. As an intermediary between image features and categories, we introduce the notion...
Recently, semantic image retrieval has attracted large amount of interest due to the rapid growth of digital image storage. However, existing approaches have severe limitations. In this paper, a new approach to digital image retrieval using intermediate semantic features and multistep search has been proposed. Instead of looking for human level semantics which is too challenging at this stage, the...
Road extraction research has always been an active research on automatic identification of remote sensing images. In this paper, improving the traditional algorithm, the author presents a new method which uses multi-weighted terms to judge the road edges, makes full use of the physical characteristics of the road, and makes the context of road edge pixels as a judgment, in order to recognize the edge...
Content-based image retrieval has become an important part of information retrieval technology. Images can be viewed as high dimensional data and are usually represented by their low-level features. How to effectively find the semantic meanings of images is a central challenge in the area. In this paper, we propose an interactive platform for region-based image clustering and retrieval. A genetic...
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