Tanveer Siddiqui - Academia.edu (original) (raw)
Uploads
Papers by Tanveer Siddiqui
Proceedings of International Conference on Cognitive …, 2004
Zenodo (CERN European Organization for Nuclear Research), Apr 18, 2019
Migration letters, Feb 17, 2024
2023 3rd International conference on Artificial Intelligence and Signal Processing (AISP)
ACM SIGIR Forum, 2006
With the explosive growth of information, it is becoming increasingly difficult to retrieve the r... more With the explosive growth of information, it is becoming increasingly difficult to retrieve the relevant documents with statistical means only. This begets new challenges to IR community and motivates researchers to look for intelligent Information Retrieval (IR) systems that search and/or filter information automatically based on some higher level of understanding are required. This higher level of understanding can only be achieved through processing of text based on semantics, which is not possible by considering a document as a "bag of words". We make a humble effort in this direction by investigating techniques that attempt to utilize semantics to improve effectiveness in IR. The hypothesis is that with an improved representation of documents and by incorporating limited semantic knowledge, it is possible to improve the effectiveness of an IR system.We propose the use of Conceptual Graph (CG) formalism for representing text. The level of semantic details to be capture...
Techniques and Technologies
Traditionally newspapers, bill boards, radio and television have been preferred media for adverti... more Traditionally newspapers, bill boards, radio and television have been preferred media for advertisement. The advent of Internet has led to the new way of advertising, on-line advertising (also known as web /Internet advertising). Its wide coverage and low cost as compared to traditional form of advertising mediums makes it quite attractive. Many organizations are spending significant amount of their advertisement budget on it. As mentioned in Broder et al. (2007) the total advertisement cost was estimated over 17 billion dollars in United States alone in 2006 with yearly
Studies in big data, Oct 14, 2017
Medical images are of high importance and patient data must be kept confidential. In this chapter... more Medical images are of high importance and patient data must be kept confidential. In this chapter, we discuss a new hybrid transform domain technique for medical image watermarking and provide a detailed analysis of existing image watermarking methods. The proposed method uses a combination of nonsubsampled contourlet transform (NSCT), discrete cosine transform (DCT) and singular value decomposition (SVD) to achieve high capacity, robustness and imperceptibility. This method is non blind which requires cover image in receiver to extract watermarked image. Cover and watermark images are pre-processed in order to ensure accurate extraction of watermark. In this approach, we have considered medical images as cover and electronic patient record (EPR) is used as secret message. EPR message is embedded into selected sub band of cover image with selected gain factor so that there should be a good trade off among imperceptibility, robustness and capacity. NSCT increases hiding capacity and is more resistant to geometrical attacks. The combination of NSCT with DCT and SVD enhanced the perceptual quality and security of watermarked image. Experimental demonstration proved that the proposed method provides high robustness against geometrical and signal processing attacks in terms of peak signal to noise ratio (PSNR) and correlation coefficient (CC).
Advances in intelligent systems and computing, Dec 25, 2015
Transform domain Steganography techniques embed secret message in significant areas of cover imag... more Transform domain Steganography techniques embed secret message in significant areas of cover image. These techniques are generally more robust against common image processing operations. In this paper, we propose an image Steganography method using singular value decomposition (SVD) and integer wavelet transform (IWT). SVD and IWT strengthen the performance of image Steganography and improve the perceptual quality of Stego images. Results have been taken over standard image data sets and compared with discrete cosine transform (DCT) and redundant discrete wavelet transform (RDWT) based image Steganography methods using peak signal to noise ratio (PSNR) correlation coefficients (CC) metrics. Experimental results show that the proposed SVD and IWT based method provides more robustness against image processing and geometric attacks, such as JPEG compression, low-pass filtering, median filtering, and addition of noise, scaling, rotation, and histogram equalization.
The International Arab Journal of Information Technology, 2015
Word Sense Disambiguation (WSD) is the task of computational assignment of correct sense of a pol... more Word Sense Disambiguation (WSD) is the task of computational assignment of correct sense of a polysemous word in a given context. This paper compares three WSD algorithms for Hindi WSD based on corpus statistics. The first algorithm, called corpus-based lesk, uses sense definitions and a sense tagged training corpus to learn weights of Content Words (CWs). These weights are used in the disambiguation process to assign a score to each sense. We experimented with four metrics for computing weight of matching words Term Frequency (TF), Inverse Document Frequency (IDF), Term Frequency-Inverse Document frequency (TF-IDF) and CW in a fixed window size. The second algorithm uses conditional probability of words and phrases co-occurring with each sense of an ambiguous word in disambiguation. The third algorithm is based on the classification information model. The first method yields an overall maximum precision of 85.87% using TF-IDF weighting scheme. The WSD algorithm using word co-occurrence statistics results in an average precision of 68.73%. The WSD algorithm using classification information model results in an average precision of 76.34%. All the three algorithms perform significantly better than direct overlap method in which case we achieve an average precision of 47.87%.
Content-based image retrieval systems were introduced as an alternative to avoid the need of manu... more Content-based image retrieval systems were introduced as an alternative to avoid the need of manual tagging in traditional keyword-based image retrieval systems. However, the representation of image using visual features only involves a loss of information which is referred to as semantic gap. A number of techniques have been proposed to deal with ‘semantic gap’. This paper reviews existing approaches to handle the well-known ‘semantic gap’ problem in image retrieval systems with a particular focus to approaches based on text and image fusion. Keywords— Image retrieval, Semantic Image Retrieval, CBIR, Text and Image fusion.
Studies in Big Data, 2017
Medical images are of high importance and patient data must be kept confidential. In this chapter... more Medical images are of high importance and patient data must be kept confidential. In this chapter, we discuss a new hybrid transform domain technique for medical image watermarking and provide a detailed analysis of existing image watermarking methods. The proposed method uses a combination of nonsubsampled contourlet transform (NSCT), discrete cosine transform (DCT) and singular value decomposition (SVD) to achieve high capacity, robustness and imperceptibility. This method is non blind which requires cover image in receiver to extract watermarked image. Cover and watermark images are pre-processed in order to ensure accurate extraction of watermark. In this approach, we have considered medical images as cover and electronic patient record (EPR) is used as secret message. EPR message is embedded into selected sub band of cover image with selected gain factor so that there should be a good trade off among imperceptibility, robustness and capacity. NSCT increases hiding capacity and is more resistant to geometrical attacks. The combination of NSCT with DCT and SVD enhanced the perceptual quality and security of watermarked image. Experimental demonstration proved that the proposed method provides high robustness against geometrical and signal processing attacks in terms of peak signal to noise ratio (PSNR) and correlation coefficient (CC).
Advances in Intelligent Systems and Computing, 2015
Transform domain Steganography techniques embed secret message in significant areas of cover imag... more Transform domain Steganography techniques embed secret message in significant areas of cover image. These techniques are generally more robust against common image processing operations. In this paper, we propose an image Steganography method using singular value decomposition (SVD) and integer wavelet transform (IWT). SVD and IWT strengthen the performance of image Steganography and improve the perceptual quality of Stego images. Results have been taken over standard image data sets and compared with discrete cosine transform (DCT) and redundant discrete wavelet transform (RDWT) based image Steganography methods using peak signal to noise ratio (PSNR) correlation coefficients (CC) metrics. Experimental results show that the proposed SVD and IWT based method provides more robustness against image processing and geometric attacks, such as JPEG compression, low-pass filtering, median filtering, and addition of noise, scaling, rotation, and histogram equalization.
2012 2nd International Conference on Power, Control and Embedded Systems, 2012
ABSTRACT
Proceedings of International Conference on Cognitive …, 2004
Zenodo (CERN European Organization for Nuclear Research), Apr 18, 2019
Migration letters, Feb 17, 2024
2023 3rd International conference on Artificial Intelligence and Signal Processing (AISP)
ACM SIGIR Forum, 2006
With the explosive growth of information, it is becoming increasingly difficult to retrieve the r... more With the explosive growth of information, it is becoming increasingly difficult to retrieve the relevant documents with statistical means only. This begets new challenges to IR community and motivates researchers to look for intelligent Information Retrieval (IR) systems that search and/or filter information automatically based on some higher level of understanding are required. This higher level of understanding can only be achieved through processing of text based on semantics, which is not possible by considering a document as a "bag of words". We make a humble effort in this direction by investigating techniques that attempt to utilize semantics to improve effectiveness in IR. The hypothesis is that with an improved representation of documents and by incorporating limited semantic knowledge, it is possible to improve the effectiveness of an IR system.We propose the use of Conceptual Graph (CG) formalism for representing text. The level of semantic details to be capture...
Techniques and Technologies
Traditionally newspapers, bill boards, radio and television have been preferred media for adverti... more Traditionally newspapers, bill boards, radio and television have been preferred media for advertisement. The advent of Internet has led to the new way of advertising, on-line advertising (also known as web /Internet advertising). Its wide coverage and low cost as compared to traditional form of advertising mediums makes it quite attractive. Many organizations are spending significant amount of their advertisement budget on it. As mentioned in Broder et al. (2007) the total advertisement cost was estimated over 17 billion dollars in United States alone in 2006 with yearly
Studies in big data, Oct 14, 2017
Medical images are of high importance and patient data must be kept confidential. In this chapter... more Medical images are of high importance and patient data must be kept confidential. In this chapter, we discuss a new hybrid transform domain technique for medical image watermarking and provide a detailed analysis of existing image watermarking methods. The proposed method uses a combination of nonsubsampled contourlet transform (NSCT), discrete cosine transform (DCT) and singular value decomposition (SVD) to achieve high capacity, robustness and imperceptibility. This method is non blind which requires cover image in receiver to extract watermarked image. Cover and watermark images are pre-processed in order to ensure accurate extraction of watermark. In this approach, we have considered medical images as cover and electronic patient record (EPR) is used as secret message. EPR message is embedded into selected sub band of cover image with selected gain factor so that there should be a good trade off among imperceptibility, robustness and capacity. NSCT increases hiding capacity and is more resistant to geometrical attacks. The combination of NSCT with DCT and SVD enhanced the perceptual quality and security of watermarked image. Experimental demonstration proved that the proposed method provides high robustness against geometrical and signal processing attacks in terms of peak signal to noise ratio (PSNR) and correlation coefficient (CC).
Advances in intelligent systems and computing, Dec 25, 2015
Transform domain Steganography techniques embed secret message in significant areas of cover imag... more Transform domain Steganography techniques embed secret message in significant areas of cover image. These techniques are generally more robust against common image processing operations. In this paper, we propose an image Steganography method using singular value decomposition (SVD) and integer wavelet transform (IWT). SVD and IWT strengthen the performance of image Steganography and improve the perceptual quality of Stego images. Results have been taken over standard image data sets and compared with discrete cosine transform (DCT) and redundant discrete wavelet transform (RDWT) based image Steganography methods using peak signal to noise ratio (PSNR) correlation coefficients (CC) metrics. Experimental results show that the proposed SVD and IWT based method provides more robustness against image processing and geometric attacks, such as JPEG compression, low-pass filtering, median filtering, and addition of noise, scaling, rotation, and histogram equalization.
The International Arab Journal of Information Technology, 2015
Word Sense Disambiguation (WSD) is the task of computational assignment of correct sense of a pol... more Word Sense Disambiguation (WSD) is the task of computational assignment of correct sense of a polysemous word in a given context. This paper compares three WSD algorithms for Hindi WSD based on corpus statistics. The first algorithm, called corpus-based lesk, uses sense definitions and a sense tagged training corpus to learn weights of Content Words (CWs). These weights are used in the disambiguation process to assign a score to each sense. We experimented with four metrics for computing weight of matching words Term Frequency (TF), Inverse Document Frequency (IDF), Term Frequency-Inverse Document frequency (TF-IDF) and CW in a fixed window size. The second algorithm uses conditional probability of words and phrases co-occurring with each sense of an ambiguous word in disambiguation. The third algorithm is based on the classification information model. The first method yields an overall maximum precision of 85.87% using TF-IDF weighting scheme. The WSD algorithm using word co-occurrence statistics results in an average precision of 68.73%. The WSD algorithm using classification information model results in an average precision of 76.34%. All the three algorithms perform significantly better than direct overlap method in which case we achieve an average precision of 47.87%.
Content-based image retrieval systems were introduced as an alternative to avoid the need of manu... more Content-based image retrieval systems were introduced as an alternative to avoid the need of manual tagging in traditional keyword-based image retrieval systems. However, the representation of image using visual features only involves a loss of information which is referred to as semantic gap. A number of techniques have been proposed to deal with ‘semantic gap’. This paper reviews existing approaches to handle the well-known ‘semantic gap’ problem in image retrieval systems with a particular focus to approaches based on text and image fusion. Keywords— Image retrieval, Semantic Image Retrieval, CBIR, Text and Image fusion.
Studies in Big Data, 2017
Medical images are of high importance and patient data must be kept confidential. In this chapter... more Medical images are of high importance and patient data must be kept confidential. In this chapter, we discuss a new hybrid transform domain technique for medical image watermarking and provide a detailed analysis of existing image watermarking methods. The proposed method uses a combination of nonsubsampled contourlet transform (NSCT), discrete cosine transform (DCT) and singular value decomposition (SVD) to achieve high capacity, robustness and imperceptibility. This method is non blind which requires cover image in receiver to extract watermarked image. Cover and watermark images are pre-processed in order to ensure accurate extraction of watermark. In this approach, we have considered medical images as cover and electronic patient record (EPR) is used as secret message. EPR message is embedded into selected sub band of cover image with selected gain factor so that there should be a good trade off among imperceptibility, robustness and capacity. NSCT increases hiding capacity and is more resistant to geometrical attacks. The combination of NSCT with DCT and SVD enhanced the perceptual quality and security of watermarked image. Experimental demonstration proved that the proposed method provides high robustness against geometrical and signal processing attacks in terms of peak signal to noise ratio (PSNR) and correlation coefficient (CC).
Advances in Intelligent Systems and Computing, 2015
Transform domain Steganography techniques embed secret message in significant areas of cover imag... more Transform domain Steganography techniques embed secret message in significant areas of cover image. These techniques are generally more robust against common image processing operations. In this paper, we propose an image Steganography method using singular value decomposition (SVD) and integer wavelet transform (IWT). SVD and IWT strengthen the performance of image Steganography and improve the perceptual quality of Stego images. Results have been taken over standard image data sets and compared with discrete cosine transform (DCT) and redundant discrete wavelet transform (RDWT) based image Steganography methods using peak signal to noise ratio (PSNR) correlation coefficients (CC) metrics. Experimental results show that the proposed SVD and IWT based method provides more robustness against image processing and geometric attacks, such as JPEG compression, low-pass filtering, median filtering, and addition of noise, scaling, rotation, and histogram equalization.
2012 2nd International Conference on Power, Control and Embedded Systems, 2012
ABSTRACT