This paper studies a based on morphological corrosion and expansion of the operation principle,application of watershed algorithm overlap image segmentation algorithm of red blood *** algorithm firstly use 4 neighborh...
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This paper studies a based on morphological corrosion and expansion of the operation principle,application of watershed algorithm overlap image segmentation algorithm of red blood *** algorithm firstly use 4 neighborhood and 8 neighborhood structures of overlapping cell image elements,through continuous alternate corrosion calculation of cells after corrosion area and the area ratio of the cells to control the number of consecutive *** separation of cell image which is based on the principle of watershed algorithm of expanding between cells *** algorithm is mainly aimed at the characteristics of red circle,from the experiment results,the overlap cells are separated,which validated the algorithm for image segmentation overlap with good red.
In this paper, a new watershed algorithm based on prior knowledge is presented for the recognition of binary images of conjoint grains of rice by machine vision. First, an algorithm for component labeling is used...
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In this paper, a new watershed algorithm based on prior knowledge is presented for the recognition of binary images of conjoint grains of rice by machine vision. First, an algorithm for component labeling is used to find whole com ponents of the conjoint grains of rice in each binary image. After the components of all the single grains are removed from each binary image according to their area threshold (AT), only the components of the conjoint grains remain, which are marked by Ms. The remaining components of the conjoint grains are then separated from each other by the watershedalgorithm where the threshold (ET) of the efficient erosion times is set, and the corresponding segmented components are marked by Mc. Finally, the union of Ms and Mc is considered as the result of recognition of binary images with conjoint grains. Over 95% of connected rice particles are correctly segmented, which indicates that the proposed method is valid and efficient.
2D gel electrophoresis (2DGE) plays an important role in proteomics. It can separate proteins effectively with their pl values and molecular weights. Proteornics researchers needed to identify interested protein spots...
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ISBN:
(纸本)9789604741083
2D gel electrophoresis (2DGE) plays an important role in proteomics. It can separate proteins effectively with their pl values and molecular weights. Proteornics researchers needed to identify interested protein spots by examining the gel. This is time consuming and labor extensive. It is desired that the computer can analyze the proteins automatically by first detecting and quantifying the protein spots in the digitized 2DGE images. In our work, we will investigate the use of the watershed algorithm in segmenting the protein spots from the varying background. However, the watershed algorithm often produces an over-segmented result. So, we will introduce the notion of fuzzy relations to improve the segmentation result.
with the characteristics of precision edge and closed contour, watershed segmentation algorithm is used widely in image segmentation. However, over-segmentation always occurs when it is applied to ultrasound images as...
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ISBN:
(纸本)9781424429011
with the characteristics of precision edge and closed contour, watershed segmentation algorithm is used widely in image segmentation. However, over-segmentation always occurs when it is applied to ultrasound images associated with speckle noise. In this paper, an improved watershed segmentation scheme is proposed based on comprehensive consideration of gray scale information, edge information and the relationship between neighboring regions of ultrasound images. A novel criteria deciding the relationship between neighboring regions was defined, and edge information was also added to the merging guidelines. Similar region merging was then applied to the initial segmentation results. The proposed scheme was tested using representative ultrasound image. The experimental results show that the proposed scheme can produce accurate contours and overcome the over-segmentation phenomenon availably.
In this paper, a new color segmentation scheme of microscopic color images is proposed. The approach combines a region growing method and a clustering method. Each channel plane of the color images is represented by a...
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ISBN:
(纸本)9789898111692
In this paper, a new color segmentation scheme of microscopic color images is proposed. The approach combines a region growing method and a clustering method. Each channel plane of the color images is represented by a set of regions using a watershed algorithm. Those regions are represented and modeled by a Region Adjacency Graph (RAG). A novel method is introduced to simplify the RAG by merging candidate regions until the violation of a stopping aggregation criterion determined using a statistical method which combines the generalized likelihood ratio (GLR) and the Bayesian information criterion (BIC). From the resulting segmented and simplified images, the RGB, image is computed. Structural features as cells area, shape indicator and cells color are extracted using the simplified graph and then stored in a database in order to elaborate meaningful queries. A regularization step based on the use of an automatic classification will take place. Results show that our method that does not involve any a priori knowledge is suitable for several types of cytology images.
The Fundus images of retina of human eye can provide valuable information about human health. In this respect, one can systematically assess digital retinal photographs, to predict various diseases. This eliminates th...
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ISBN:
(纸本)9783540928409
The Fundus images of retina of human eye can provide valuable information about human health. In this respect, one can systematically assess digital retinal photographs, to predict various diseases. This eliminates the need for manual assessment of ophthalmic images in diagnostic practices. This work studies how the changes in the retina caused by Central Serous Retinopathy (CSR) can be detected from color fundus images using image-processing techniques. Localization of the leakage area is usually accomplished by Fluorescein angiography. The proposed work is motivated by severe discomfort occurring to certain patients by the injection of fluorescein dye and also the increase in occurrence of CSR now days. This paper presents a novel segmentation algorithm for automatic detection of leakage site in color fundus images of retina. Wavelet transform method is used for denoising in the preprocessing stage. Contrast Enhancement method is employed for non-uniform illumination compensation and enhancement. The work determines CSR by the localization of leakage pinpoint in terms of pixel co-ordinates and calculates the area of the leakage site from normal color fundus images itself.
with the characteristics of precision edge and closed contour, watershed segmentation algorithm is used widely in image segmentation. However, over-segmentation always occurs when it is applied to ultrasound images as...
详细信息
with the characteristics of precision edge and closed contour, watershed segmentation algorithm is used widely in image segmentation. However, over-segmentation always occurs when it is applied to ultrasound images associated with speckle noise. In this paper, an improved watershed segmentation scheme is proposed based on comprehensive consideration of gray scale information, edge information and the relationship between neighboring regions of ultrasound images. A novel criteria deciding the relationship between neighboring regions was defined, and edge information was also added to the merging guidelines. Similar region merging was then applied to the initial segmentation results. The proposed scheme was tested using representative ultrasound image. The experimental results show that the proposed scheme can produce accurate contours and overcome the over-segmentation phenomenon availably.
This paper describes three cytological image segmentation methods. The analysis includes the watershed algorithm, active contouring and a cellular automata GrowCut method. One can also find here a description of image...
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This paper describes three cytological image segmentation methods. The analysis includes the watershed algorithm, active contouring and a cellular automata GrowCut method. One can also find here a description of image pre-processing, Hough transform based pre-segmentation and an automatic nuclei localization mechanism used in our approach. Preliminary experimental results collected on a benchmark database present the quality of the methods in the analyzed issue. The discussion of common errors and possible future problems summarizes the work and points out regions that need further research.
An effective scheme for stereoscopic video object segmentation was presented based on depth and edge information. Disparity estimation algorithm using region information was firstly proposed to get reliable depth info...
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ISBN:
(纸本)9780819467676
An effective scheme for stereoscopic video object segmentation was presented based on depth and edge information. Disparity estimation algorithm using region information was firstly proposed to get reliable depth information. In. the proposed method, a new adaptive-size window approach was introduced to stereo matching in order to overcome problems with fixed-size window. Then, an improved watershed algorithm was exploited to achieve initial segmentation of depth image and coarse object areas were obtained. For each depth segments, edge detection was implemented to obtain accurate contours of object. Finally, watershed algorithm was utilized to segment object again. Using the extracted objects, an efficient motion tracking algorithm based on region was performed to track the video objects of the rest frames. The experimental results show that the proposed method can get good disparity map and segment video objects successfully.
As is known, agriculture is very important in China, but the problem about pests has hampered the further development of Chinese agriculture. Digital image-processing technology and mathematical morphology are referre...
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ISBN:
(纸本)9780387772523
As is known, agriculture is very important in China, but the problem about pests has hampered the further development of Chinese agriculture. Digital image-processing technology and mathematical morphology are referred to as the main research methods, and tiny pets like aphids among field are referred to as the research objects. Image processing technology such as edge-enhancing diffusion filtering, mathematical morphology and watershed segmentation algorithm is used to monitor pest population density, which greatly raises efficiency of pest data acquisition. After the segmentation of the image of the pests, the number of the insect individuals can be obtained from the background by using image processing technology. Computer image processing technology provides a possibility to solve this problem and becomes a very important direction to monitor regional pest population density.
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