International Journal of Innovative Research in Computer and Communication Engineering

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TITLE Facial Composite Analysis and Generate for Forensic
ABSTRACT Traditional forensic sketching is timeconsuming and dependent on skilled artists, limiting its integration with automated recognition systems. A sketch generation application that simplifies suspect face creation by providing an interactive drag-and-drop feature selection interface. By leveraging deep learning and cloud-based processing, the system matches sketches with law enforcement databases to improve identification accuracy and reduce investigation time.
AUTHOR LAKSHMI A M, LAKSHMI M L, LAVANYA P, LOCHANA G, VEENA H S UG Students, Dept. of CSE, Jain Institute of Technology Davangere, Karnataka, India Assistant Professor, Dept. of CSE, Jain Institute of Technology, Davangere, India
VOLUME 177
DOI DOI: 10.15680/IJIRCCE.2025.1312103
PDF pdf/103_Facial Composite Analysis and Generate for Forensic.pdf
KEYWORDS
References [1] B. Sheng, P. Li, C. Gao, and K.-L. Ma, “Deep representation guided face sketch synthesis,” IEEE Transactions on Visualization and Computer Graphics, vol. 25, no. 12, pp. 3216–3230, Dec. 2019.
[2] Y. J. Huang, W. C. Lin, I. C. Yeh, and T. Y. Lee, “Geometric and textural blending for 3D model stylization,” IEEE Transactions on Visualization and Computer Graphics, vol. 24, no. 2, pp. 1114–1126, Feb. 2018.
[3] Y. C. Lai, B. A. Chen, K. W. Chen, W. L. Si, C. Y. Yao, and E. Zhang, “Data-driven NPR illustrations of natural flows in Chinese painting,” IEEE Transactions on Visualization and Computer Graphics, vol. 23, no. 12, pp. 2535–2549, Dec. 2017.
[4] S. S. Lin, C. C. Morace, C. H. Lin, L. F. Hsu, and T. Y. Lee, “Generation of Escher arts with dual perception,” IEEE Transactions on Visualization and Computer Graphics, vol. 24, no. 2, pp. 1103–1113, Feb. 2018.
[5] A. M. Rodriguez, L. Unzueta, Z. Geradts, M. Worring, and U. Elordi, “Multi-task explainable quality networks for large-scale forensic facial recognition,” IEEE J. Sel. Topics Signal Process., 2023.
[6] M. A. Silva and G. C. Chávez, “Face sketch recognition from local features,” in 27th SIBGRAPI Conf. on Graphics, Patterns and Images, 2014, pp. 57–64.
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