A Novel Approach for Intellectual Image Retrieval Based on Image Content Using ANN

This paper deals with a novel approach for intellectual Image Retrieval (IIR) based on image content analysis using Artificial Neural Network. The Multilayer Back Propagation Feed Forward algorithm is proposed for interactive image retrieval, which takes query by image as an input and retrieves the most relevant images from the image dataset. The content based semantic features are extracted for around 500 images from image corpus and applied for training of the Neural Network. The outcome of the rigorous experimentations reveals that application of ANN for IIR enhances the effectiveness of the performance of image retrieval.

[1]  Matthieu Cord,et al.  Active Learning Methods for Interactive Image Retrieval , 2008, IEEE Transactions on Image Processing.

[2]  Sitalakshmi Venkatraman,et al.  MapReduce neural network framework for efficient content based image retrieval from large datasets in the cloud , 2012, 2012 12th International Conference on Hybrid Intelligent Systems (HIS).

[3]  Loay Edwar George,et al.  Tissues image retrieval system based on co-occuerrence, run length and roughness features , 2013, 2013 International Conference on Computer Medical Applications (ICCMA).

[4]  Frank S. Marzano,et al.  Empirical algorithms to retrieve surface rain-rate from Special Sensor Microwave Imager over a mid-latitude basin , 2002, IEEE International Geoscience and Remote Sensing Symposium.

[5]  M. Esmel ElAlami,et al.  A new matching strategy for content based image retrieval system , 2014, Appl. Soft Comput..

[6]  Muhammad Moinuddin,et al.  Image Retrieval Based on Color and Texture Feature Using Artificial Neural Network , 2012 .

[7]  Dai Ran,et al.  A Sufficient and Necessary Condition for the Absolute Consistency of XML DTDs , 2007, Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007).

[8]  A. Chilambuchelvan,et al.  A hybrid approach to extract scene text from videos , 2012, 2012 International Conference on Computing, Electronics and Electrical Technologies (ICCEET).

[9]  Ayoub Al-Hamadi,et al.  Cubic-splines neural network- based system for Image Retrieval , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[10]  Silvana G. Dellepiane,et al.  Design and Implementation of Web-Based Systems for Image Segmentation and CBIR , 2006, IEEE Transactions on Instrumentation and Measurement.

[11]  Eduardo Ferreira Ribeiro,et al.  High-Level Semantic Based Image Characterization Using Artificial Neural Networks , 2007, Seventh International Conference on Intelligent Systems Design and Applications (ISDA 2007).

[12]  Mohamad Awad,et al.  Sea water chlorophyll-a estimation using hyperspectral images and supervised Artificial Neural Network , 2014, Ecol. Informatics.

[13]  Kandarpa Kumar Sarma,et al.  Multilevel-DWT based image de-noising using feed forward artificial neural network , 2014, 2014 International Conference on Signal Processing and Integrated Networks (SPIN).

[14]  B. Williams,et al.  Artificial intelligence for explosive ordnance disposal system (AI-EOD) , 1992, [Proceedings 1992] IJCNN International Joint Conference on Neural Networks.

[15]  Kien A. Hua,et al.  A Lazy Processing Approach to User Relevance Feedback for Content-Based Image Retrieval , 2010, 2010 IEEE International Symposium on Multimedia.

[16]  Guoqiang Peter Zhang,et al.  Neural networks for classification: a survey , 2000, IEEE Trans. Syst. Man Cybern. Part C.

[17]  A. I. Wuryandari,et al.  Gathering information realtime and anywhere (GIRA) using an ANN algorithm , 2012, 2012 International Conference on System Engineering and Technology (ICSET).

[18]  Xiong Xiao,et al.  A Load-Balancing Self-Organizing Incremental Neural Network , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[19]  A. Murari,et al.  New Techniques and Technologies for Information Retrieval and Knowledge Extraction from Nuclear Fusion Massive Databases , 2007, 2007 IEEE International Symposium on Intelligent Signal Processing.

[20]  Larry R. Medsker,et al.  Hybrid Intelligent Systems , 1995, Springer US.

[21]  Fatos T. Yarman-Vural,et al.  Learning similarity space , 2002, Proceedings. International Conference on Image Processing.

[22]  Discriminating lithology in arctic environments from Earth orbit, an evaluation of satellite imagery and classification algorithms , 2001 .

[23]  Petri Koistinen,et al.  Using additive noise in back-propagation training , 1992, IEEE Trans. Neural Networks.

[24]  Eugenio Di Sciascio,et al.  Content-Based Image Retrieval over the Web Using Query by Sketch and Relevance Feedback , 1999, VISUAL.

[25]  Leandro Augusto Silva,et al.  Pattern recognition in mammographic images used by the residents in mammography , 2013, 2013 International Conference on Computer Medical Applications (ICCMA).

[26]  Urszula Markowska-Kaczmar,et al.  Emotion-based image retrieval—An artificial neural network approach , 2010, Proceedings of the International Multiconference on Computer Science and Information Technology.

[27]  Jiakui Tang,et al.  Aerosol retrieval from remote sensing image using artificial neural network , 2010, 2010 International Conference on Computer Application and System Modeling (ICCASM 2010).

[28]  T. Ouarda,et al.  Artificial neural network based model for retrieval of the direct normal, diffuse horizontal and global horizontal irradiances using SEVIRI images , 2013 .