TY - GEN
T1 - License plate recognition part II
T2 - 2012 4th International Conference on Intelligent and Advanced Systems, ICIAS 2012
AU - Boudjella, Aissa
AU - Samir, Brahim Belhaouari
AU - Daud, H. Bt
AU - Syahira, Raja
PY - 2012
Y1 - 2012
N2 - In this paper, we have developed car licence plate recognition for parking system, based on symelets 8 wavelet transform for features extraction and k-Nearest Neighbours for classification. The system is implemented and simulated in MATLAB, and its performance is tested on real image using Euclidean distance method. The proposed system consists of three steps:1) image acquisition module which captures the image of a moving car regions, 2) image processing module for extraction and classification, and 3)database that handles the car information. This method gives better recognition rate of 96% at the threshold Tc0.4. More importantly, the present results show that the number of wavelet coefficient decreases as the threshold increases. Thus, the computation time can be reduced considerably which will make this method faster and robust. Increasing the level from 5 to 6, does not affect significantly the accuracy and the computation time.
AB - In this paper, we have developed car licence plate recognition for parking system, based on symelets 8 wavelet transform for features extraction and k-Nearest Neighbours for classification. The system is implemented and simulated in MATLAB, and its performance is tested on real image using Euclidean distance method. The proposed system consists of three steps:1) image acquisition module which captures the image of a moving car regions, 2) image processing module for extraction and classification, and 3)database that handles the car information. This method gives better recognition rate of 96% at the threshold Tc0.4. More importantly, the present results show that the number of wavelet coefficient decreases as the threshold increases. Thus, the computation time can be reduced considerably which will make this method faster and robust. Increasing the level from 5 to 6, does not affect significantly the accuracy and the computation time.
KW - Euclidian distance method
KW - License plate
KW - Pattern recognition
KW - classification
KW - feature extraction
KW - k-Nearest Neighbors
KW - wavelet transform
UR - http://www.scopus.com/inward/record.url?scp=84867950500&partnerID=8YFLogxK
U2 - 10.1109/ICIAS.2012.6306103
DO - 10.1109/ICIAS.2012.6306103
M3 - Conference contribution
AN - SCOPUS:84867950500
SN - 9781457719677
T3 - ICIAS 2012 - 2012 4th International Conference on Intelligent and Advanced Systems: A Conference of World Engineering, Science and Technology Congress (ESTCON) - Conference Proceedings
SP - 695
EP - 700
BT - ICIAS 2012 - 2012 4th International Conference on Intelligent and Advanced Systems
Y2 - 12 June 2012 through 14 June 2012
ER -