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General Information
    • ISSN: 2301-3559
    • Frequency: Quarterly
    • DOI: 10.18178/LNSE
    • Editor-in-Chief: Prof. Jemal Antidze
    • Executive Editor: Ms. Nina Lee
    • Abstracting/ Indexing: EI (INSPEC, IET), DOAJ, Electronic Journals Library, Engineering & Technology Digital Library, Ulrich's Periodicals Directory, International Computer Science Digital Library (ICSDL), ProQuest and Google Scholar.
    • E-mail: lnse@ejournal.net
Editor-in-chief
Prof. Jemal Antidze
I. Vekua Scientific Institute of Applied Mathematics
Tbilisi State University, Georgia
I'm happy to take on the position of editor in chief of LNSE. We encourage authors to submit papers concerning any branch of Software Engineering.

LNSE 2013 Vol.1(1): 94-97 ISSN:2301-3559
DOI: 10.7763/LNSE.2013.V1.21

Analysis of Ultra Sound Kidney Image Features for Image Retrieval by Gray Level Co-Occurrence Matrices

S. Manikandan, V. Rajamani, and N. Murugan

Abstract—Medical imaging is though expensive because of capital costs, is easy to perform because of its noninvasive nature. In order to provide better analysis and diagnosis, various features have been extracted from any images. In this paper many important features of the ultra sound kidney images have been extracted and analysis has been made for the proposed image retrieval from the image database. Quantitative establishment of use the features for detection of abnormalities in Ultra sound kidney images have been made. Here, we made an analysis that the texture has been used to discriminate among the various types of tissue in image applications. Various important features namely contrast, homogeneity, correlation, energy, autocorrelation, variance, co-variance, inertia, promenance, shade, dissimilarity, inverse difference moment (IDM), maximum probability and entropy have been extracted and analyzed for the application in connection of a image database for the image retrieval process.

Index Terms—Extraction, features, statistical test image retrieval, ultra sound kidney image.

S. Manikandan is with the Departement of Computer Applications, R.M.D. Engineering College, Kavaraipettai, Chennai, Tamil nadu, India. (e-mail: smk76dgl@gmail.com).
V. Rajamani is with the Indra Ganesan College of Engineering, Trichy, Tamil nadu, India.
N. Murugan is with the P.S.N.A. College of Engineering and Technology, Dindigul, Tamil nadu, India.

[PDF]

Cite: S. Manikandan, V. Rajamani, and N. Murugan, "Analysis of Ultra Sound Kidney Image Features for Image Retrieval by Gray Level Co-Occurrence Matrices," Lecture Notes on Software Engineering  vol. 1, no. 1, pp. 94-97, 2013.

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