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Real-Time scale-invariant license plate detection using cascade classifiers
, Article 2nd International Conference on Multimedia Information Processing and Retrieval, MIPR 2019, 28 March 2019 through 30 March 2019 ; Pages 399-402 , 2019 ; 9781728111988 (ISBN) ; Nazem Deligani, A. H ; Jafari Amirbandi, J ; Karimzadeh Kiskani, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
This paper presents an online scale-invariant license plate detection (LPD) system with high accuracy for the automatic license plate recognition (ALPR) systems. A dataset of Persian plates is accumulated with more than 44,000 images of plates and 9000 frames of real world roads. For the plate detection and localization, a multi-stage classifier is trained with local binary pattern (LBP) features and a multi-scale algorithm to detect plates with any size within a frame. Besides, we proposed multiple algorithms to boost the performance and accuracy of our solution, including two-stage detection, background subtraction for non-moving areas elimination, and a sophisticated method for estimating...
AdaBoost-based face detection in color images with low false alarm
, Article ICCMS 2010 - 2010 International Conference on Computer Modeling and Simulation, 22 January 2010 through 24 January 2010, Sanya ; Volume 2 , 2010 , Pages 107-111 ; 9780769539416 (ISBN) ; Kasaei, S ; Sharif University of Technology
2010
Abstract
In this paper, we have proposed a new face detection method which combines the AdaBoost algorithm with skin color information and support vector machine (SVM). First, a cascade classifier based on AdaBoost is used to detect faces in images. Due to noise and illumination changes some nonfaces might be detected too, therefore we have used a skin color model in the YCbCr color space to remove some of the detected nonfaces. Finally, we have utilized SVM to detect faces more accurately. Experimental results show that the performance of the proposed method is higher than the basic AdaBoost in the sense of detecting fewer nonfaces