Issue |
MATEC Web of Conferences
Volume 57, 2016
4th International Conference on Advancements in Engineering & Technology (ICAET-2016)
|
|
---|---|---|
Article Number | 02002 | |
Number of page(s) | 6 | |
Section | Information Systems & Computer Science Engineering | |
DOI | https://doi.org/10.1051/matecconf/20165702002 | |
Published online | 11 May 2016 |
A Novel Technique for Shape Feature Extraction Using Content Based Image Retrieval
BGIET, Dept. of CSE, Sangrur, India
Corresponding author: er.jaspreetdhanoa@gmail.com
With the advent of technology and multimedia information, digital images are increasing very quickly. Various techniques are being developed to retrieve/search digital information or data contained in the image. Traditional Text Based Image Retrieval System is not plentiful. Since it is time consuming as it require manual image annotation. Also, the image annotation differs with different peoples. An alternate to this is Content Based Image Retrieval (CBIR) system. It retrieves/search for image using its contents rather the text, keywords etc. A lot of exploration has been compassed in the range of Content Based Image Retrieval (CBIR) with various feature extraction techniques. Shape is a significant image feature as it reflects the human perception. Moreover, Shape is quite simple to use by the user to define object in an image as compared to other features such as Color, texture etc. Over and above, if applied alone, no descriptor will give fruitful results. Further, by combining it with an improved classifier, one can use the positive features of both the descriptor and classifier. So, a tryout will be made to establish an algorithm for accurate feature (Shape) extraction in Content Based Image Retrieval (CBIR). The main objectives of this project are: (a) To propose an algorithm for shape feature extraction using CBIR, (b) To evaluate the performance of proposed algorithm and (c To compare the proposed algorithm with state of art techniques.
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.