Human face detection in excessive dark image by using contrast stretching, histogram equalization and adaptive equalization

  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract

    Darkness is the inverse state of the brightness, is obtained as an absence of noticeable light and illumination. Generally, face detection applications cannot detect any human face in a dark image, where the image has captured from the dark environment or dark night. In this manuscript, we demonstrate our experiment, where we use Contrast Stretching, Histogram Equalization and Adaptive Equalization techniques for detecting any human face in any dark image. In this paper, we also illustrate our proposed algorithm, working procedure and differentiate the pixel intensity of different stage of image processing. We essentially do this research from an application perspective, where a software application detects the human face from a dark photo or a very low-contrast image and the photo has been captured from an excessive dark environment.



  • Keywords

    Image Processing; Dark Image; Face Detection; Low-Contrast Image; Computer Vision.

  • References

      [1] Android Central Forums. (2017) Facial Recognition does not work in Dark. [Online]. Available:

      [2] (2017) Face ID not recognising me in low light conditions/at night. [Online]. Available:

      [3] C. E. Proctor, W. Parks, B. S. Riggan, A conceptual illustration for thermal-to-visible synthesis for interoperability with existing visible-based facial recognition systems, U.S. Army Research Laboratory, United States, 2018.

      [4] B. S. Riggan, N. J. Short, S. Hu, “Thermal to Visible Synthesis of Face Images using Multiple Regions”, in Proc. 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), Lake Tahoe, NV, USA, 2018, pp. 30–38.

      [5] J. Lezama, Q. Qiu, G. Sapiro, “Not Afraid of the Dark: NIR-VIS Face Recognition via Cross-spectral Hallucination and Low-rank Embedding”, in Proc. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), United States, Honolulu, HI, USA, 2017, pp. 6628–6637.

      [6] E. Komagal, V. Seenivasan, K. Anand, C. P. A. Raj, “Human Detection In Hours Of Darkness Using Gaussian Mixture Model Algorithm”, International Journal of Information Sciences and Techniques (IJIST), vol. 4, No. 3, pp. 83–89, May 2014.

      [7] S. Singh, A. Godara, Gaurav, “Detection of Partial Invisible Objects in Images using Histogram Equalization”, International Journal of Computer Applications, vol. 85, No. 9, pp. 40–44, January 2014.

      [8] N. Dong, Z. Jia, J. Shao, Z. Li, F. Liu, J. Zhao, P.Y. Peng, “Adaptive Object Detection and Visibility Improvement in Foggy Image”, Journal of Multimedia, vol. 6, No. 1, pp. 14–21, February 2011.

      [9] A. H. Foruzan, Y.W. Chen, R. A. Zoroofi, A. Furukawa, Y. Sato, M. Hori, N. Tomiyama, “Segmentation of Liver in Low-Contrast Images Using K-Means Clustering and Geodesic Active Contour Algorithms”, IEICE Transactions on Information and Systems, vol. E96.D, No. 4, pp. 798–807, April 2013.

      [10] S. S. Al-amri, “Contrast Stretching Enhancement in Remote Sensing Image”, BIOINFO Sensor Networks, vol. 1, No. 1, Article Id: BIA0001652, pp. 6–9, December 2011.

      [11] S. S. Al-amri, N. V. Kalyankar, S. D. Khamitkar “A Comparative Study of Removal Noise from Remote Sensing Image”, International Journal of Computer Science Issues (IJCSI), vol. 7, Issue 1, No. 1, pp. 32–36, January 2010.

      [12] C.P. Loizou, M. Pantziaris, I. Seimenis, C.S. Pattichis, “Brain MR Image Normalization in Texture Analysis of Multiple Sclerosis”, in Proc. 9th International Conference on Information Technology and Applications in Biomedicine, Larnaca, Cyprus, November 2009.

      [13] M. Zohaib, A. Shan, A. U. Rahman, H. ALi, “Image Enhancement by using Histogram Equalization Technique in Matlab”, International Journal of Advanced Research in Computer Engineering & Technology, vol. 7, No. 2, pp. 150–154, February 2018.

      [14] Y. Zhu, C. Huang, “An Adaptive Histogram Equalization Algorithm on the Image Gray Level Mapping”, Physics Procedia, vol. 25, pp. 601 – 608, December 2012.

      [15] R. Chouhan, R. K. Jha, P. K. Biswas, “Enhancement of dark and low-contrast images using dynamic stochastic resonance”, IET Image Processing, vol. 7, No. 2, pp. 174–184, March 2013.

      [16] M. T. Deole, S. P. Hingway, S. S. Suresh, “Dynamic Stochastic Resonance Technique for Enhancement of Low Contrast Images”, International Journal of Application or Innovation in Engineering & Management (IJAIEM), vol. 3, No. 1, pp. 174–184, January 2014.

      [17] R. K. Jha, R. Chouhan, P. K. Biswas, “Noise-induced Contrast Enhancement of Dark Images using Non-dynamic Stochastic Resonance”, in Proc. National Conference on Communications (NCC), 2012.

      [18] A. R. Rivera, B. Ryu, O. Chae, “Content-Aware Dark Image Enhancement Through Channel Division”, IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 21, No. 9, pp. 3967–3980, September 2012.

      [19] C. H. Shen, H. H. Chen, “Robust Focus Measure for Low-Contrast Images”, in Proc. 2006 Digest of Technical Papers International Conference on Consumer Electronics, Las Vegas, NV, USA, 2006, pp. 69–70.

      [20] H.S. Tae, C.-S. Park, B.-G. Cho, J.-W. Han, B. J. Shin, S. Chien, D. H. Lee, “Driving Waveform for Reducing Temporal Dark Image Sticking in AC Plasma Display Panel Based on Perceived Luminance”, IEEE Transactions on Plasma Science, vol. 34, No. 3, pp. 996–1003, June 2006.

      [21] R. Fisher, S. Perkins, A. Walker, E. Wolfart. (2003) Contrast Stretching. [Online]. Available:

      [22] Department of Mathematics, University of California, Irvine. (2008) Histogram equalization. [Online]. Available:

      [23] S. M. Pizer, E. P. Amburn, J. D. Austin, R. Cromartie, A. Geselowitz, T. Greer, B. H. Romeny, J. B. Zimmerman, K. Zuiderveld, “Adaptive Histogram Equalization and Its Variations”, Computer Vision, Graphics, and Image Processing, vol. 39, No. 3, pp. 355– 368, Sept. 1987.

      [24] E. A. Haller, “Adaptive histogram equalization in GIS”, Annals of the University of Craiova, Mathematics and Computer Science Series, vol. 38, No. 1, pp. 100–104, March 2011.

      [25] K. Goyal, K. Agarwal, R. Kumar, “Face detection and tracking: Using OpenCV”, in Proc. 2017 International conference of Electronics, Communication and Aerospace Technology (ICECA), Coimbatore, India, 2017, pp. 474–478.

      [26] S.V. Viraktamath, M. Katti, A. Khatawkar, P. Kulkarni, “Face Detection and Tracking using OpenCV”, The SIJ Transactions on Computer Networks & Communication Engineering, vol. 1, No. 3, pp. 45–50, July-August 2013.

      [27] R. Mustafa, Y. Min, D. Zhu, “Obscenity Detection Using Haar-Like Features and Gentle Adaboost Classifier”, The Scientific World Journal, vol. 2014, Article ID: 753860, pp. 1–6, June 2014.

      [28] T. Kumar, K. Verma, “A Theory Based on Conversion of RGB image to Gray image”, International Journal of Computer Applications, vol. 7, No. 2, pp. 7–10, September 2010.

      [29] A. Mordvintsev, A. K. Revision. OpenCV-Python Tutorials. (2015) Drawing Functions in OpenCV. [Online]. Available:

      [30] OpenCV. (2018) Cascade Classification. [Online]. Available:

      [31] P. I. Wilson, J. Fernandez, “Facial feature detection using Haar classifiers”, Journal of Computing Sciences in Colleges, vol. 21, No. 4, pp. 127–133, April 2006.

      [32] OpenCV. (2015) Changing Colorspaces. [Online]. Available:

      [33] H. Kuang, L. Chen, F. Gu, J. Chen, L. L. H. Chan, H. Yan, “Combining region of interest extraction and image enhancement for nighttime vehicle detection”, IEEE Intelligent Systems, vol. 31, No. 3, pp. 57–65, May 2016.

      [34] S. v. d. Walt, J. L. Schonberger, F. Boulogne, J. D. Warner, N. Yager, E. Gouillart, T. Yu and the scikit-image contributors, “scikit-image: image processing in Python”, PeerJ 2:e453, June 2014.

      [35] OpenCV. (2018) Face Detection using Haar Cascades. [Online]. Available:

      [36] H. Gujar, P. Mhatre, S. Ghanate, S. Chile, S. Kadam, D. Kurle, S. Shitole, “Python Based Image Processing”, SNDT Women's University, Mumbai, January 2016.

      [37] M. F. A. Bhuiyan, R. R. Rothi, “Image visualization in extreme dark environment and face detection”, B.Sc. Thesis, Department of Software Engineering, Daffodil International University, Bangladesh, 2018.

      [38] Smart Data Science Center (SDSC), Daffodil International University. (2018) [Online]. Available:




Article ID: 13713
DOI: 10.14419/ijet.v7i4.13713

Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.