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Automatic endoscope video analysis is an essential function for medical robot and computer-aided diagnosis system. However, the performance of these video analysis algorithms are often degraded by low quality endoscope images under the uncontrolled environment, where some of them are difficult even for human ourselves for analysis, such as over-saturated by reflection, too dark or obscure. In this...
Cell image segmentation is one of the hot topics in medical image processing. Most of the classical cell image segmentation algorithms perform the segmentation directly on the original image and result in the loss of the cell nuclei with low intensity contrast. To solve this problem, this paper presents a novel nuclei segmentation method. Based on analyzing the characteristics of the cell nuclei,...
Detection of bare-hand touch interacting with projector-camera system requires accurate and robust foreground extraction, which is challenging with the complex background and the continuous alteration of environmental illuminant. In this paper, a novel approach is proposed for precise hand segmentation based on combination of regional segmentation and saliency estimation that is computed by global...
In order to avoid the over-segmentation problem caused by original watershed transform and improve the segmentation precision of Mycobacterium Tuberculosis (MTB) images, a novel segmentation algorithm is proposed based on automatic-marker watershed transform. The automatic marker is accomplished by Gaussian weighted adaptive threshold segmentation and local minimum points search within gradient image...
In this paper, we propose a novel learning-based approach for single image dehazing. The proposed approach is mostly inspired by the observation that the color of the objects fades gradually along with the increment of the scene depth. We regard the RGB values of the pixels within the image as the important feature, and use the back propagation neural network to mine the internal link between color...
According to the distribution characteristics of lidar collection points, dense in the vicinity and sparse in the distance, a terrain classification method based on variable-scale three-dimensional grid map is proposed to classify an unknown terrain into four categories, which includes roads, lawns, buildings and trees. First, we establish a variable-scale three-dimensional grid map. Then the algorithm...
Haze is one of the most common atmospheric phenomena. In hazy weather, smoke, dust and other dry particles obscure the clarity of the scenery objects severely degrading the quality of the outdoor images taken by camera. Moreover, most outdoor vision applications such as video-surveillance systems and traffic monitoring systems fail to work normally in this condition. Therefore, improving the technique...
This paper presents a novel image haze removal approach from single image. In the algorithm, the constant albedo and dark channel prior methods are combined to represent the transmission model of hazed image. And then, the quick shift segmentation approach is introduced to decompose the input image into some gray level consistent areas. Compared with traditional fixed image partition schemes, better...
This study aims at development of pneumatic soft devices for stomach X-ray examination. Generally stomach X-ray examination can be divided two procedures roughly. One is observation of condition of back-side stomach wall and the other is that of front-side stomach wall. In this paper, two types of soft devices for each examination have been developed. The devices are configured with pneumatic actuators...
The vision system of the mobile robot is a low-level function that provides the required target information of the current environment for the upper vision tasks. The real-time performance and robustness of object segmentation in cluttered environments is still a serious problem in robot visions. In this paper, a new real-time indoor scene segmentation method based on RGB-D image, is presented and...
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