Object based Image Retrieval with Segmentation and Extraction of Features using various Methods
Laxmidevi Noolvi1, M.V. Sudhamni2

1Laxmidevi Noolvi, Department of CSE, RNSIT, Bangalore (Karnataka), India.

2Dr. M V Sudhamani, ISE, RNSIT, Bangalore (Karnataka), India.

Manuscript received on 03 December 2019 | Revised Manuscript received on 11 December 2019 | Manuscript Published on 31 December 2019 | PP: 92-98 | Volume-9 Issue-2S December 2019 | Retrieval Number: B10591292S19/2019©BEIESP | DOI: 10.35940/ijitee.B1059.1292S19

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: This paper proposes Object Based Image Retrieval (OBIR) System with segmenting the objects from the images and then extracting various features from the objects. The objects are the most prominent part of an image which relates more to the human perception. First, the object present in the images is segmented by four different segmentation techniques such as K-means, Active Contours, Edge-Convex hull and Global Thresholding. Later, the color features such as Color Histogram (CH) and Color Coherence Vector (CCV), Texture feature using Local Binary Patterns (LBP) and shape feature using Histogram of Gradients (HOG) are extracted. Finally, with the usage of different segmentation and techniques mentioned above feature are extracted from objects. Results obtained are tabulated and performance study is made.

Keywords: OBIR, Color Histogram, Color Coherence Vector and Local Binary Patterns and Histogram of Gradients.
Scope of the Article: Information Retrieval