Open Access Open Access  Restricted Access Subscription or Fee Access

Recognition of Vehicle Number Plate Using Mathematical Morphology and Neural Networks

Madhavi R Bichwe, Sureshwari Bichwe


This paper presents a method for recognition of the vehicle number plate from the image using neural networks and mathematical morphology. The main theme is to use different morphological operations in such a way so that the number plate of the vehicle can be extracted efficiently. The technique makes the extraction of the plate independent of color, location and size of number plate. The proposed approach can be divided into simple processes, which are, image enhancement, morphing transformation, morphological gradient, combination of resultant images and extracting the number plate from the objects that are left in the image. Then segmentation is applied to recognize the plate using neural network. This algorithm can quickly and correctly recognize the number plate from the vehicle image.

Full Text:



S. Du, M. Ibrahim, M. Shehata, W. Badawy. Automatic license plate recognition (ALPR): a state-of-the-art review, IEEE Trans Circ Syst Video Technol. 2013; 23(2): 311–25p.

N. Sulaiman. Development of automatic vehicle plate detection system, In: 3rd International Conference on System Engineering and Technology. 2013, 130–5p.

S. Shaikh, B. Lahiri, G. Bhatt, N. Raja. A novel approach for automatic number plate recognition, International Conference on Intelligent Systems and Signal Processing (ISSP). 2013, 275–380p.

R. Azad, H.R. Shayegh. New method for optimization of license plate recognition system with use of edge detection and connected component, In: 3rd International Conference on Computer and Knowledge Engineering (ICCKE). 2013, 21–5p.

N. Owamoyo, A. Alaba Fadele, and A. Abudu. Number plate recognition for Nigerian vehicles, Acad Res Int J (ARIJ). 2013; 4(3): 48–55p.

S. Kaur, S. Kaur. n Efficient approach for number plate extraction from vehicles images under image processing, Int J Comput Sci Inform Technol. 2014; 5(3)


  • There are currently no refbacks.