CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Article:Skeleton based Signatures for Content based Image Retrieval

by M. Narayana, Sandeep V.M, Subhash Kulkarni
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 23 - Number 7
Year of Publication: 2011
Authors: M. Narayana, Sandeep V.M, Subhash Kulkarni
10.5120/2898-3793

M. Narayana, Sandeep V.M, Subhash Kulkarni . Article:Skeleton based Signatures for Content based Image Retrieval. International Journal of Computer Applications. 23, 7 ( June 2011), 29-34. DOI=10.5120/2898-3793

@article{ 10.5120/2898-3793,
author = { M. Narayana, Sandeep V.M, Subhash Kulkarni },
title = { Article:Skeleton based Signatures for Content based Image Retrieval },
journal = { International Journal of Computer Applications },
issue_date = { June 2011 },
volume = { 23 },
number = { 7 },
month = { June },
year = { 2011 },
issn = { 0975-8887 },
pages = { 29-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume23/number7/2898-3793/ },
doi = { 10.5120/2898-3793 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:09:33.194696+05:30
%A M. Narayana
%A Sandeep V.M
%A Subhash Kulkarni
%T Article:Skeleton based Signatures for Content based Image Retrieval
%J International Journal of Computer Applications
%@ 0975-8887
%V 23
%N 7
%P 29-34
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Content Based Image Retrieval with fast and high matching retrieving ability is the need of the day for shape mining. A simple, fast, robust, invariant and efficient Content Based image Retrieval system with shape signatures derived from skeleton, region and boundary of the object is presented. The shape signatures derived from distance mapped function are invariant to rotation and scaling.

References
  1. Bai,X.,ang,X., Yu,D..Latecti,L.J., 2008.Skeleton-Based Shape Classification Using Path similarity, International Journal of Pattern Recognition and Artificial Intelligence, Vol.22, No.4, 733-746.
  2. Chan, T.F., Vase, L.A., 2001.Active Contours without Edges, IEEE Transactions on Image Processing, Vol.10, No.2, pp266-277.
  3. Choi,W.P., Lam,K.M., Siu,W.C.,2000. an Efficient and Accurate Algorithm for Extracting a Skeleton, IEEE Xplore .
  4. Frome,A., Singer,Y., Malik,J., 2007.Image Retrieval and Classification Using Local Distance functions, Advances in Neural Information Processing,Citeseer.
  5. Ge,Y., Fitzpatrick,J,M.,1996.On the Generation of Skeleton from Discrete Euclidean Distance Maps, IEEE Transactions on pattern analysis & Machine Intelligence 18(11), pp.1055-1066.
  6. LandreJ., Truchetet,F., 2007.Image Retrieval with Binary Hamming Distance, Conference on Computer vision Theory,Citeseer.
  7. Malladi,R..,Sethian,j.A.,Vemuri,B.C.,1995.Shape modeling with front propagation: A level set approach, IEEE Trans. Pattern Anal. Mach. Intell.Vol.17, No.2, pp.158-175.
  8. Mercimek,D., K.Gulez,K., Velimumcu,T., 2005. Real object recognition using moment invariants, pp.765-775.
  9. Montanari, 1968. A Method for Obtaining Skeleton from Digitized Images Using a Quari- Euclidean Distance, Journal of the Association for Computing Machinary, 16(4):534-549.
  10. Mortara,M.,Patane,G.,2002.Shape-Covering for Skeleton Extraction, International Journal of Shape Modeling, Vol.8, No.2, 139-158.
  11. Nandagopalan,S.,Adiga,Dr.B.S.,deepakN.,2009.A Universal model for Content-Based Image retrieval, International Journal of computer science 4:4.
  12. Sandeep,V.M., Subhash,S.K., 2006.Curve Invariant Fast Distance Mapping Technique for Level Sets, IEEE’s ICSIP 2006, Hubli, India, 777-780.
  13. Sandeep,V.M., Subhash,s.k., 2008.Hierarchical Perceptual Segmentation using arbitrary n-phase level sets, International Journal of Applied Engineering Research, ISSN 0973-4562, 3(11): 1615-1626.
  14. Sandeep,V.M., Vinayadath Kohir., Subhash kulkarni., 2010.Level set Issues for Efficient Image Segmentation, International Journal on Image and Data Fusion, ISSN.1947-9832, 1-18, 2010.
  15. Sandeep, V.M., Narayana, M., Subhash, S.K., 2008. A Scale and Rotation Invariant Fast Image Mining for Shapes, IEEE Conference on AI TOOLS in Engineering, 6-8.
  16. Sunder,H.,Silver,D., N.Gagvani,D.,Dickinson,S., 2003.Skeleton Based Shape Matching and Retrieval, Proceedings of the Shape Modeling International
  17. Tari,Z.S.G., Shah,J., Pienh.,1997. Extraction of Shape Skeletons from Grayscale Images, Computer Vision & Image Understanding, Citeseer.
  18. Xiaofeng,S.,sherrill-Mix,A., Qigang Gao.,2007. Perceptual Shape-Based Natural Image Retrieval Representation and Retrieva, International Conference on Semantic Computing (ICSC).
  19. Zhang,D., Lu,G.,2001. Content-Based shape retrieval Using Different Shape Descriptors: A Comparative Stud, In Proc. Of IEEE Conference of Multimedia and Expo (ICME’01), Tokyo, August, pp.317-320.
  20. Zhang,D.,Yi Lim,M.C.,2007. An Efficient and Robust Technique for Region Based shape Representation and Retrieval, 6th IEEE/ACIS International Conference on Computer and Information Science (ICIS).
Index Terms

Computer Science
Information Sciences

Keywords

Skeleton Shape Signature Shape Retrieval CBIR DSFT

Powered by PhDFocusTM