**Dumitru Baleanu**

Cankaya University, Faculty of Art and Sciences Department of Mathematics and Computer Sciences, Ankara, Turkey

> Institute of Space Sciences, Magurele-Bucharest, Romania

**Part 1** 

**Signal Processing** 

**1** 

*UK*

**Real-Time DSP-Based** 

*2CitySync Ltd., Welwyn Garden City,* 

**License Plate Character Segmentation** 

Zoe Jeffrey1, Soodamani Ramalingam1 and Nico Bekooy2 *1School of Engineering and Technology, University of Hertfordshire,* 

**Algorithm Using 2D Haar Wavelet Transform** 

The potential applications of Wavelet Transform (WT) are limitless including image processing, audio compression and communication systems. In image processing, WT is used in applications such as image compression, denoising, speckle removal, feature analysis, edge detection and object detection. The use of WT algorithms in image processing for real-time custom applications may require dedicated processors such as Digital Signal Processor (DSPs), Field Programmable Gate Arrays (FPGAs) and Graphics Processing Units (GPUs) as reported in (Ma et al., 2000), (Benkrid et al., 2001) and (Wong et al., 2007)

The interest in this chapter is the use of WT in image objects segmentation, in particular, in the area of Automatic Number Plate Recognition (ANPR) also known as License Plate Recognition (LPR). ANPR algorithm is normally divided into three sections namely LP candidate detection, character segmentation and recognition. The focus of this chapter is on the use of Haar WT algorithms for License Plate (LP) character segmentation on a DSP using Standard Definition (SD) and High Definition (HD) images. This is an extension of the work reported in (Musoromy et al., 2010) by the authors, where Daubechies and Haar WT are used to detect image edges and to enhance features of an image to detect a LP region that contain characters. The work in (Musoromy et al., 2010) demonstrated that 2D Haar WT is favourable in ANPR using DSP due to its ability to operate in real-time. The drive here is the consumer interest in real-time standalone embedded ANPR systems. The next section

The chapter organisation is as follows: Section (2) reviews dedicated hardware for WTbased image processing algorithms. Section (3) gives a review of image processing techniques using WT and in ANPR application. Section (4) presents the proposed LP character segmentation algorithm based on 2D Haar WT edge detector. Section (5) presents experimental setup. Section (6) presents results and analysis. Section (7) gives conclusion

describes the proposed LP character segmentation algorithm.

and Section (8) gives references.

**1. Introduction** 

respectively.
