A Comparative Analysis of Quality Metrics between Different Image Enhancement Techniques for Facial Sketches

  • Authors

    • Swathi B Achar
    • Sannidhan M S
    • Abhir Bhandary
    https://doi.org/10.14419/ijet.v7i3.34.19562
  • Facial Sketches, Enhancement techniques, Quality metrics, PSNR, MSE, SSIM, Time complexity.
  • Enhancement of an image is considered as one of the important aspect in image processing. It is also considered to be major pre-processing step which is used in vision systems and lot many image processing applications. It is used in law enforcement application such as in crime investigation process, identification and apprehension of criminals by matching facial sketches to the mug-shot photos. Here skilled forensic artists are used to draw sketches based on the vocal description provided by the victim or eye witness. The sketches drawn might be blurred, less quality images. So to measure the quality of sketches, here three quality assessment methods are used in this study such as PSNR (Peak Signal-to-Noise Ratio), MSE (Mean Squared Error) and the SSIM (Structural Similarity index). Hence this paper aims in discovering a better image enhancement technique for the sketches from different databases by comparative analysis of aforesaid quality metrics along with their time complexity factor. The method has considered both viewed sketches and composite sketches as a source of input.

  • References

    1. [1] Narinder Kaur, Seema Baghila & Sunil Kumar (2015). A Review: Image Enhancement and various techniques. International Journal of Advances in Science Engineering and Technology, ISSN: 2321-9009 Volume- 3, Issue-3.

      [2] Kokila, R., Sannidhan, M. S., & Bhandary, A. (2017, March). A study and analysis of various techniques to match sketches to Mugshot photos. In Inventive Communication and Computational Technologies (ICICCT), 2017 International Conference on (pp. 41-44). IEEE.

      [3] Kokila, R., Sannidhan, M. S., & Bhandary, A. (2017, September). A novel approach for matching composite sketches to mugshot photos using the fusion of SIFT and SURF feature descriptor. In Advances in Computing, Communications and Informatics (ICACCI), 2017 International Conference on (pp. 1458-1464). IEEE.

      [4] Kipli, K., Krishnan, S., Zamhari, N., Muhammad, M. S., Masra, S. M. W., Chin, K. L., & Lias, K. (2011, March). Full reference image quality metrics and their performance. In Signal Processing and its Applications (CSPA), 2011 IEEE 7th International Colloquium on (pp. 33-38). IEEE.

      [5] Cheng, Y., Pedersen, M., & Chen, G. (2017, September). Evaluation of image quality metrics for sharpness enhancement. In Image and Signal Processing and Analysis (ISPA), 2017 10th International Symposium on (pp. 115-120). IEEE.

      [6] Lal, S., & Chandra, M. (2014). Efficient algorithm for contrast enhancement of natural images. Int. Arab J. Inf. Technol., 11(1), 95-102.

      [7] de Freitas Zampolo, R., & Seara, R. (2005, September). A comparison of image quality metric performances under practical conditions. In Image Processing, 2005. ICIP 2005. IEEE International Conference on (Vol. 3, pp. III-1192). IEEE.

      [8] Suneetha, M. I., & Venkateswarlu, D. T. (2012). Image enhancement through contrast improvement using a linear parameterized gradient intercept model. ARPN Journal of Engineering and Applied Scinces (ARPN-JEAS), Website: www. arpnjournals. com (ISSN 1819-6608) Volume, 7, 945-949.

      [9] Stark, J. A. (2000). Adaptive image contrast enhancement using generalizations of histogram equalization. IEEE Transactions on image processing, 9(5), 889-896.

      [10] Ruikar, J. D., Sinha, A. K., & Chaudhury, S. (2014, February). Image quality assessment algorithms: study and performance comparison. In Electronics and Communication Systems (ICECS), 2014 International Conference on (pp. 1-4). IEEE.

      [11] Sannidhan, M. S., & Ananth Prabhu, G. “A Comprehensive Review on Various State-Of-The-Art Techniques for Composite Sketch Matching.†Imperial Journal of Interdisciplinary Research (IJIR), 2.12(2016):1131-1138.

      [12] FACES 4.0, IQ Biometrix, http://www.iqbiometrix.com, 2011.

      [13] Identi-Kit, Identi-Kit Solutions, http://www.identikit.net/, 2011

      [14] X. Wang and X. Tang, “Face Photo-Sketch Synthesis and Recognition,†IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Vol. 31, 2009.

      [15] Scott Klum, Hu Han, Brendan Klare, and Anil K. Jain. The FaceSketchID System: Matching Facial Composites to Mugshots. IEEE Transaction on Information Forensics and Security (TIFS), vol. 9, no. 12, pp. 2248-2263, Dec. 2014.

  • Downloads

  • How to Cite

    B Achar, S., M S, S., & Bhandary, A. (2018). A Comparative Analysis of Quality Metrics between Different Image Enhancement Techniques for Facial Sketches. International Journal of Engineering & Technology, 7(3.34), 794-798. https://doi.org/10.14419/ijet.v7i3.34.19562