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Ahmad Reza Eskandari
Sharif University of Technology
Computer Science & IT Electrical & Electronics Engineering

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A Novel Semantic Statistical Model for Automatic Image Annotation Using the Relationship between the Regions Based on Multi-Criteria Decision Making Hengame Deljooi; Ahmad Reza Eskandari
International Journal of Electrical and Computer Engineering (IJECE) Vol 4, No 1: February 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

Automatic image annotation has emerged as an important research topic due to the existence of the semantic gap and in addition to its potential application on image retrieval and management.  In this paper we present an approach which combines regional contexts and visual topics to automatic image annotation. Regional contexts model the relationship between the regions, whereas visual topics provide the global distribution of topics over an image. Conventional image annotation methods neglected the relationship between the regions in an image, while these regions are exactly explanation of the image semantics, therefore considering the relationship between them are helpful to annotate the images. The proposed model extracts regional contexts and visual topics from the image, and incorporates them by MCDM (Multi Criteria Decision Making) approach based on TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution) method. Regional contexts and visual topics are learned by PLSA (Probability Latent Semantic Analysis) from the training data. The experiments on 5k Corel images show that integrating these two kinds of information is beneficial to image annotation.DOI:http://dx.doi.org/10.11591/ijece.v4i1.4598
Defect Detection of Tiles Based On High Frequency Distortion Afsaneh Fathi; Ahmad Reza Eskandari
International Journal of Electrical and Computer Engineering (IJECE) Vol 3, No 4: August 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

Quality control in Tiles Industry is of great importance. Therefore, it is effective to improve an automatic inspection system, instead of manpower, to increase accuracy and velocity and decrease costs. To this end, a new method to segment tile surfaces is offered in this study. This method aims at detecting defective areas in a tile, based on extracting features of edge defects. This method is based on the idea that human eye can better perceive the defects in a tile by looking at its edges. In the proposed method, first, in order to extract frequency characteristics resistant against transference, Undecimated Discrete Wavelet Packets transform is applied on images. Later, by computing local entropy values on high-frequency sub-bands images, those which appropriately include images defects are chosen to extract statistical features. Finally, Back propagation neural network method is used to determine segmented images containing defective areas. The obtained results, both visually and computationally indicates the higher efficacy of this method compared with the related state of the art methods.DOI:http://dx.doi.org/10.11591/ijece.v3i4.3014
A Robust Steganography method Using Adjustable Parameters Ahmad Reza Eskandari
International Journal of Electrical and Computer Engineering (IJECE) Vol 3, No 2: April 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

In this paper, a new steganography method based on contourlet transform is presented. Compared with the previous works, the proposed method causes far fewer distortions in high frequency coefficients. This significantly increases the quality of stegano image and extracted secret image and its robustness against to steganalysis algorithm. Furthermore, we proposed two adjustable parameters that could be suited in direction of changing the quality of stegano image and extracted secret images or its robustness against to attacks and steganalysis algorithms. Using these parameters, much better performance of storing data is accessible. The proposed algorithm has higher robustness against to steganalysis algorithm in comparison with related state of the art methods. Likewise, the experimental results show robustness respect to Gaussian noise and other attacks such as JPEG compression.DOI:http://dx.doi.org/10.11591/ijece.v3i2.2236
Co-Authors Afsaneh Fathi Hengame Deljooi