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    Gaussian and Gabor Filter Approach for Object Segmentation

    Source: Journal of Computing and Information Science in Engineering:;2014:;volume( 014 ):;issue: 002::page 21006
    Author:
    Thilagamani, S.
    ,
    Shanthi, N.
    DOI: 10.1115/1.4026458
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The problem of segmenting the object from the background is addressed in the proposed Gaussian and Gabor Filter Approach (GGFA) for object segmentation. An improved and efficient approach based on Gaussian and Gabor Filter reads the given input image and performs filtering and smoothing operation. The region occupied by the object is extracted from the image by performing various operations like bilateral filtering, Edge detection, Clustering, and Region growing. The proposed approach experimented on standard images taken from Caltech datasets, Corel Photo CDs, and Weizmann horse datasets show significantly improved results.
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      Gaussian and Gabor Filter Approach for Object Segmentation

    URI
    https://yetl.yabesh.ir/yetl1/handle/yetl/154225
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    • Journal of Computing and Information Science in Engineering

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    contributor authorThilagamani, S.
    contributor authorShanthi, N.
    date accessioned2017-05-09T01:06:05Z
    date available2017-05-09T01:06:05Z
    date issued2014
    identifier issn1530-9827
    identifier otherjcise_014_02_021006.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/154225
    description abstractThe problem of segmenting the object from the background is addressed in the proposed Gaussian and Gabor Filter Approach (GGFA) for object segmentation. An improved and efficient approach based on Gaussian and Gabor Filter reads the given input image and performs filtering and smoothing operation. The region occupied by the object is extracted from the image by performing various operations like bilateral filtering, Edge detection, Clustering, and Region growing. The proposed approach experimented on standard images taken from Caltech datasets, Corel Photo CDs, and Weizmann horse datasets show significantly improved results.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleGaussian and Gabor Filter Approach for Object Segmentation
    typeJournal Paper
    journal volume14
    journal issue2
    journal titleJournal of Computing and Information Science in Engineering
    identifier doi10.1115/1.4026458
    journal fristpage21006
    journal lastpage21006
    identifier eissn1530-9827
    treeJournal of Computing and Information Science in Engineering:;2014:;volume( 014 ):;issue: 002
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian