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[2] Lapo Governi, Rocco Furferi, Matteo Palai, Yary Volpe, “3D geometry reconstruction from orthographic views: A method based on 3D image processing and data fitting”Computers in Industry, Volume 64, Issue 9, December 2013, Pages 1290-1300, ISSN 0166-3615,
[3] http://dx.doi.org/10.1016/j.compind.2013.02.003.
[4] Passarella, Rossi, Astri Agustina, Sutarno Sutarno, Kemahyanto Exaudi, and Junkani Junkani. "Design Concept of State-Chart Method Application through Robot Motion Equipped With Webcam Features as E-Learning Media for Children." (2013): 115-120.
[5] Shipp, John I. "LED illumination system for endoscopic cameras." U.S. Patent No. 6,449,006. 10 Sep. 2002.
[6] Otsu, Nobuyuki. "A threshold selection method from gray-level histograms." Automatica 11.285-296 (1975): 23-27.
[7] Rianmora, Suchada, and Pisut Koomsap. "Recommended slicing positions for adaptive direct slicing by image processing technique." The International Journal of Advanced Manufacturing Technology 46.9-12 (2010): 1021-1033.
[8] RAMIREZ, Carlos Alejo, PEREZ, Manuel David. Face detection and analysis of facial expressions.
[9] LECUMBERRY, R., Federico. Calculation of disparity and segmentation of objects in video sequences. Master's thesis in electrical engineering. University of the Republic Montevideo, Uruguay. August 3, 2005
[10] LI, Yadong, GOSHTASBY, Ardeshir y GARCIA, Oscar. Detecting and tracking human faces in videos. Wright State University, 2000.
[11] FERIS, Rogerio, EMIDIO DE CAMPOS, Teofilo y MARCONDES, Cesar. Detection and tracking of facial features in video sequences. Lecture Notes in Artificial Intelligence, Vol. 1793, pp. 197-206, 2000.
[12] HABILI, Nariman. Automatic segmentation of the face and hands in sign language video sequences. Technical report, Adelaide University, Australia, 2001.
[13] ROWLEY, Henry, BALUJA, Shumeet, and KANADE, Takeo. Neural network-based face detection. IEEE, 1998.
[14] VIOLA, Paul y JONES, Michael. Robust Real-Time Face Detection. International Journal of Computer Vision, Vol.57, No.2, pp 137-154, 2004.
[15] CASTRILLON, M., DENIZ, O., GUERRA, C., and HERNÁNDEZ, M. "ENCARA2: Real-time detection of multiple faces at different resolutions in video streams". ELSEVIER, Journal Visual Communication and Image Representation. Article in press (2007).
[16] BARTLETT, Marian Stewart et al. Real-time face detection and facial expression recognition: development and applications to human-computer interaction. University of California, USA, 2004.
[17] SILAPACHOTE, P, KARUPPIAH, D y HANSON, A. Feature selecting using AdaBoost for face expression recognition. University of Massachusetts Amherst, USA.
[18] BELAROUSSI, Rachid and MILGRAM, Maurice. Face detecting and skin color based tracking: a comparative study. University Pierre an Maire Curie. Paris, Francia, 2007.
[19] IEEE Standar Glossary for Image Processing and Pattern recognition Terminology. Published by the Institute of Electrical and Electronics Engineers, New York, USA, 1990.
[20] SCHAPIRE, R and FREUND, Y. A decision theoretic generalization of online learning and application to boosting. AT&T Bell Laboratories. USA, 1995.
[21] PAPAGEORGIOU,C., OREN,M. and POGGIO,T. A general framework for object detection. Proceedings of International Conference on Computer Vision, Enero de 1998, Bombay, India.
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Affiliations
Alhamzawi Hussein Ali Mezher
University of Debrecen
Faces and eyes Detection in Digital Images Using Cascade Classifiers
Abstract
In this Article we present a way to implementation and detect the face and eyes on digital image, based on Haar-like features extraction and cascade classifier, these techniques used in 100 % and 92% for faces and eyes detection respectively for the best all cases using low processing time , we used cheap equipment in our work (Acer TravelMate web camera ) . OpenCV library(computer vision library) and Python language used in this work.