Super-Pixel
Diabetes detection using segmentation of super pixel in slo images
... utilized Super pixel division it improves the future assessments that accommodating to test the proposed approach against option smoothing techniques and other spatially touchy endmember detection ...
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Content based Intelligent Image Retrieval Based on Super Pixel with Wavelet Transform
... on super pixel with multi-resolution image. Super pixel plays an important role in image retrieval since instead single pixels a group of pixel in an image called super ...
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Super Pixel Segmentation with Nakagami Model for SAR Images M. Rangaswamy, G. Ragasudha, P. surekha, G. Ghousiyabhanu, G. Manasa
... the super pixels' centroids. Super pixel division itself may not get the job done to speak to a whole ...a super pixel portrayal of picture, we characterize the super pixels as ...
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A novel density-based super-pixel aggregation for automatic segmentation of remote sensing images in urban areas
... un-segmented super-pixels are merged as a group of ...the super-pixels were segmented based on vegetation and height ...single super-pixel were selected, and based on their NDVI and nDSM ...
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Review of Advanced Color Image Segmentation Using K-means and Super-pixel Algorithm
... image and considers the distance between each data. The characteristic of data clustering is that each pixel of a cluster does not certainly connective. The basis method of data clustering can be divided into ...
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SPECTRAL-SPATIAL CLASSIFICATION OF SPECTRAL IMAGES WITH SUPER PIXEL-BASED DISCRIMINATIVE SPARES MODEL
... A super pixel-based discriminative sparse model (SBDSM) is proposed to effectively exploit the spatial information of the ...each super pixel by utilizing the joint sparse ...1) super ...
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Title : Optic Disc and Optic Cup Detection Using Super Pixel Classification Based on PCA & Mathematical MorphologyAuthor (s) :Sreelakshmi B L, M.Deepa
... Abstract: GLAUCOMA is a chronic eye disease in which the optic nerve is progressively damaged and it leads to vision loss.. It is the second leading cause of blindness. As it cannot be cured, detecting the disease in ...
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Super pixel Based Line operator for Retinal Blood Vessel Segmentation
... a super-pixel based line operator is proposed as to recognize lines and the edges, and in this way permits more resistance in the position of the particular ...
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An Efficient Image Forensic Mechanism using Super Pixel by SIFT and LFP Algorithm
... its pixel. The author has described the two kinds of image pixel based forgery detection scheme along with the copy move forgery detection (deals with only shifting of copied ...
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Improved Information for Endoscopy Diseases Using K Mean and Super Pixel Segmentation in Wireless Endoscopy Dataset
... Canny Edge Detector is well known for its ability to generate single-pixel thick continuous edges. It has four inputs: Input image I, value of smoothing parameter sigma, high threshold Th and low threshold Thl. ...
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An Automatic Computer Aided Diagnostic System for the Analysis of Glaucoma Using Super pixel Classification and Clustering Methods
... A region of interest (ROI) is a portion of an image that you want to filter or perform some other operation on. An ROI by creating a binary mask, which is a binary image that is the same size as the image you want to ...
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Robust joint sparsity model for hyperspectral image classification
... robust super-pixel level joint sparse representation classification model (RSJSRC) to address the mixed noise problem in sparsity-based HSI clas- ...
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COMPARATIVE STUDY ON OPTIC DISC SEGMENTATION TECHNIQUES
... From fig 4, it is found that the precision rate value for Super pixel method is greater than the level set method. In this metric, true positive is one in which the case is positive and identified as ...
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Salient Object Detection via Combining Duplex Features
... a pixel and all other pixels, the time complexity will suddenly rise to O ...one pixel block, and detect the salient area of the image by the difference between the pixel ...a super- ...
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Glaucoma Recogination Using Superpixel Classification and Artificial Neural Network
... each pixel, this is the key to *speeding up the algorithm because the number of distance calculations can be reduced significantly by limiting the size of the search region significantly reduces, and results in a ...
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MRI Reconstruction using Compressive Sensing : A Review Paper
... The group sparse method, which exploits additional sparse representations of the spatial group structure, can increase the degrees of sparsity, as a result better reconstruction performance can be obtained. In [10] , an ...
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LITERATURE REVIEW ON ENERGY CONSUMPTION AND CONSERVATION IN MOBILE DEVICE
... and super pixel based simple linear Iterative clustering (SLIC) algorithms are proposed to accomplish the segmentation ...based super pixel segmentation outperforms the watershed ...
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Object Detection Using Probabilistic Graph Model
... Abstract-- We propose a Probabilistic Graph based Model for interactive image segmentation. A multilayer probabilistic Graph is constructed from an oversegmentation of the image to model the relationships among ...
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A Novel Integrated Method for Detection of Salient Regions in an Image using HDCT
... Next calculate the feature vectors for every super pixel, use a classification algorithm to check whether each region is salient. In this study, the use of random forest classification because of its ...
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Super Resolution Land Cover Pattern Prediction Using a Hopfield Neural Network
... Traditionally, classification approaches have focused on ‘hard’, one-class-per-pixel techniques (Campbell, 1996). Such approaches were found to be inaccurate, inappropriate, and an alternative approach has become ...
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