Improved image retrieval based on fuzzy colour feature vector

Ahlam M. Ben-Ahmeida; Ahmed Y. Ben Sasi

doi:10.1117/12.2021159

14 March 2013 Improved image retrieval based on fuzzy colour feature vector

Ahlam M. Ben-Ahmeida, Ahmed Y. Ben Sasi

Proceedings Volume 8768, International Conference on Graphic and Image Processing (ICGIP 2012); 87686C (2013) https://doi.org/10.1117/12.2021159
Event: 2012 International Conference on Graphic and Image Processing, 2012, Singapore, Singapore

Abstract

One of Image indexing techniques is the Content-Based Image Retrieval which is an efficient way for retrieving images from the image database automatically based on their visual contents such as colour, texture, and shape. In this paper will be discuss how using content-based image retrieval (CBIR) method by colour feature extraction and similarity checking. By dividing the query image and all images in the database into pieces and extract the features of each part separately and comparing the corresponding portions in order to increase the accuracy in the retrieval. The proposed approach is based on the use of fuzzy sets, to overcome the problem of curse of dimensionality. The contribution of colour of each pixel is associated to all the bins in the histogram using fuzzy-set membership functions. As a result, the Fuzzy Colour Histogram (FCH), outperformed the Conventional Colour Histogram (CCH) in image retrieving, due to its speedy results, where were images represented as signatures that took less size of memory, depending on the number of divisions. The results also showed that FCH is less sensitive and more robust to brightness changes than the CCH with better retrieval recall values.

Citation Download Citation

Ahlam M. Ben-Ahmeida and Ahmed Y. Ben Sasi "Improved image retrieval based on fuzzy colour feature vector", Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 87686C (14 March 2013); https://doi.org/10.1117/12.2021159

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available