Conference Papers

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Author: search.filters.author.Muhammed, A.

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    A Novel Fingerprint Image Enhancement based on Super Resolution
    (Institute of Electrical and Electronics Engineers Inc., 2020) Muhammed, A.; Pais, A.R.
    Fingerprint is a most common and broadly accepted biometric trait used for personal authentication. In fingerprint-based authentication, the feature extraction module extract features, and these extracted characteristics are used for authentication. In fingerprints, the feature extraction module heavily depends on the status of the image. However, in practice, always getting a good quality fingerprint image is not possible. Moreover, a notable number of fingerprints collected are of poor quality. The accurate extraction of fingerprint characteristics from a lesser quality fingerprint image is a challenging problem. Fingerprint enhancement is introduced to resolve this issue. Hence in this paper, we introduce a fingerprint enhancement technique using a Deep Convolution Neural Network (DCNN), which improves image quality. The proposed method consists of super-resolution, followed by filtering and enhancement. The proposed method provides better results as compared with the conventional fingerprint enhancement methods. The experimental results determine that the proposed strategy improves the visual clarity of low-quality images and reduces the error rates during the fingerprint matching. © 2020 IEEE.
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    Impact of Rhetorical Roles in Abstractive Legal Document Summarization
    (Institute of Electrical and Electronics Engineers Inc., 2024) Muhammed, A.; Muslihuddeen, H.; Sankar, S.; Anand Kumar, M.
    This paper explores the relationships between rhetorical roles and the summarization of legal documents. By employing automated interpretation techniques, we segment legal judgment documents and identify rhetorical roles, treating it as a 13-class labeling problem. Using CRFs and a BiLSTM architecture, we extract rhetorical roles. Our study extends further by employing an ensemble summarizer to examine the impact of each rhetorical role on the summarization process and evaluate the same using ROGUE and BLEU scores. Through experimentation, we explore the impact of selecting individual rhetorical roles from the documents, thereby facilitating a comprehensive analysis of its effect on various scoring metrics. Our analysis reveals that certain roles, such as FAC and ANALYSIS, contribute significantly to summary quality, while others like ISSUE, have a less pronounced impact which interestingly also tend to be included in the summary almost verbatim, underscoring their inherent utility in the summarization process. By shedding light on this process, our research aims to equip researchers with valuable insights into streamlining summarization techniques, potentially reducing the volume of text data processed. Ultimately, these findings could pave the way for the development of more efficient summarization algorithms tailored to different roles in legal documents, enhancing accessibility and comprehension for professionals and researchers alike. © 2024 IEEE.
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    A Novel Cancelable Fingerprint Template Generation Mechanism Using Visual Secret Sharing
    (Springer Science and Business Media Deutschland GmbH, 2024) Muhammed, A.; Pais, A.R.
    In fingerprint-based authentication system, cancelable fingerprint templates are generated to defend the fingerprint information. In this paper, we proposed a novel cancelable fingerprint template using Visual Secret Sharing (VSS). Using VSS, each fingerprint image is encrypted into different shares. Finally, these shares are preserved in distinct databases and treated as fingerprint template. Traditional VSS schemes are suffering from pixel expansion and contrast reduction. We have used grid-based VSS and data embedding mechanisms to succeed these limitations. The proposed fingerprint templates satisfy ideal properties of cancelable templates such as non-invertibility, diversity, and revocability without altering the performance of the authentication system. To enhance the speed of the template generation and reconstruction, we have used General Purpose Graphical Processing Unit (GPGPU) to fulfill the operations. The experimental evaluation validates that the reconstructed fingerprints have equivalent performance as the initial fingerprints with upgraded security. © Springer Nature Switzerland AG 2024.