Abstract
Police database cannot have images of first-time offenders; hence, apprehending them becomes a very challenging task. In this paper, we propose a novel technique to apprehend first-time offenders using composite sketches and images captured by unmanned aerial vehicles. The key contribution of this paper is we have developed a new technology to match composite sketches with images captured by unmanned aerial vehicle to apprehend first-time criminals in a very short time period. The unmanned aerial vehicle is sent in the area where the first-time offender is likely to be present. The image captured by unmanned aerial vehicle is passed to face detection module so that only human faces are obtained. Feature extraction is performed using multi-resolution uniform local binary pattern, and classification is performed using dictionary matching. This proposed method is validated by composite sketches generated using SketchCop FACETTE face design system software and images captured by Phantom 3 professional unmanned aerial vehicle.
Similar content being viewed by others
References
Bhatt HS, Bharadwaj S, Singh R, Vatsa M (2012) Memetically optimized MCWLD for matching sketches with digital face images. IEEE Trans Inf Forensics Secur 7:1522–1535
Chugh T, Bhatt HS, Singh R, Vatsa M (2013a) Matching age separated composite sketches and digital face images. In: IEEE international conference on biometrics: theory, applications and systems (BTAS), pp 1–6
Fernandes SL, Bala GJ (2013b) A comparative study on ICA and LPP based Face Recognition under varying illuminations and facial expressions. In: International conference on signal processing image processing and pattern recognition (ICSIPR), pp 122–126
Fernandes SL, Bala GJ (2013c) Robust face recognition in the presence of Noises and Blurring effects by fusing appearance based techniques and sparse representation. In: IEEE international conference on advanced computing, networking and security, pp 84–89
Fernandes SL, Bala GJ (2013d) A comparative study on ICA and LPP based face recognition under varying illuminations and facial expressions. In: IEEE international conference on signal processing, image processing and pattern recognition, pp 7–8
Fernandes SL, Bala GJ (2013e) Recognizing faces when images are corrupted by varying degree of noises and blurring effects. In: Advances in intelligent systems and computing, pp 101–108
Fernandes SL, Bala GJ (2014a) Development and analysis of various state of the art techniques for face recognition under varying Poses. Recent Patents Eng 8:143–146
Fernandes SL, Bala GJ (2014b) Recognizing facial images using Gabor wavelets, DCT-neural network, hybrid spatial feature interdependence matrix. In: International conference on devices, circuits and systems (ICDCS), pp 1–5
Fernandes SL, Bala GJ (2014c) Recognizing facial images using ICA, LPP, MACE Gabor filters, score level fusion techniques. In: IEEE International conference electronics and communication systems, pp 1–5
Fernandes SL, Bala GJ (2014d) Recognizing facial images in the presence of various Noises and Blurring effects using Gabor Wavelets, DC T-Neural Network, hybrid spatial feature interdependence matrix. In: IEEE international conference on devices, circuits and systems, pp 1–5
Fernandes SL, Bala GJ (2014e) 3D and 4D face recognition: a comprehensive review. Recent Patents Eng 8:112–119
Foster I, Kesselman C, Nick J, Tuecke S (2002) The physiology of the grid: an open grid services architecture for distributed systems integration. In: Technical report, Global Grid Forum
Gross R, Matthews I, Cohn J, Kanade T, Baker S (2010) Multi-PIE. Image Vis Comput 28:807–813
Han H, Klare BF, Bonnen K, Jain AK (2013) Matching composite sketches to face photos: a component-based approach. IEEE TIFS 8:191–204
Jain AK, Li SZ (2005) Handbook of face recognition. Springer, Berlin
Joshi P, Prakash SA (2015) quality aware technique for biometric recognition. In: IEEE international conference on signal processing and integrated networks (SPIN), pp 795–800
Klare BF, Zhifeng L, Jain AK (2011) Matching forensic sketches to mug shot photos. IEEE TPAMI 33:639–646
Klum SJ, Han H, Klare BF, Jain AK (2014) The Face SketchID system: matching facial composites to mugshots. IEEE TIFS 9:2248–2263
Mittal P, Jain A, Singh R, Vatsa M (2013) Boosting local descriptors for matching composite and digital face images. In: 20th International conference on image processing, pp 2797–2801
Mittal P, Jain A, Goswami G, Singh R, Vatsa M (2014) Recognizing composite sketches with digital face images via SSD dictionary. In: IEEE international joint conference on biometrics (IJCB), pp 1–6
Nocedal J, Wright SJ (2006) Conjugate gradient methods. Springer, Berlin
Pan SJ, Yang Q (2010) A survey on transfer learning. IEEE Trans KDE 22:1345–1359
Raghavendra R, Raja KB, Yang B, Busch C (2014) Automatic face quality assessment from video using gray level co-occurrence matrix: an empirical study on automatic border control system. In: IEEE international conference on pattern recognition, pp 438–443
Rahim NN, Malek NAA, Zeki AM, Abubakar A (2014) Automatic face reconstruction system. In: International conference on computer science and information technology, pp 208–212
Shechtman E, Irani M (2007) Matching local self-similarities across images and videos. In: IEEE computer vision and pattern recognition, pp 1–8
Tieleman T (2008) Training restricted boltzmann machines using approximations to the likelihood gradient. In: ACM international conference on machine learning, pp 1064–1071
Tola E, Lepetit V, Fua P (2010) Daisy: an efficient dense descriptor applied to wide-baseline stereo. IEEE TPAMI 32:815–830
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Fernandes, S.L., Josemin Bala, G. Matching images captured from unmanned aerial vehicle. Int J Syst Assur Eng Manag 9, 26–32 (2018). https://doi.org/10.1007/s13198-016-0431-5
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13198-016-0431-5