Normal view MARC view ISBD view

Segmentation and recognition of Malaysian car plates using Freeman chain codes / Nor Amizam Jusoh

By:

Nor Amizam Jusoh

Material type: Text

TextPublication details: Kuantan, Pahang : UMP, 2011Description: xiv, 105 p. : ill. (some col.) ; 30 cm. + 1 CD-ROMISBN:

THE0002939(Local)

Subject(s):

Dissertation note: Thesis (Master of Science (Computer)) -- Universiti Malaysia Pahang - 2011 Abstract: Research on automatic car plate recognition has been widely and intensively conducted all over the world with the application of various types of segmentation and recognition techniques by researchers. Most of the recognition techniques applied are not focusing on shape-based recognition although through normal human vision, each character in the car plate has a unique and different shape with each other. The chosen techniques have contributed into many proposed suitable methodologies for car plate recognition research but with the same objectives; to gain high or increase the segmentation and recognition accuracy rate with less processing time. This research is conducted with the aim of identifying the suitable or appropriate segmentation technique which can be used to segment either the standard or non-standard specification car plates. Besides that, the objective is also to study whether the shape-based recognition technique is efficient and accurate enough to recognize Malaysian car plates which are varied in terms of font types. Techniques that have been chosen for segmentation process are pixel count, connected component labeling (CCL) and a proposed technique; the connected component labeling with minimum object removal. As for recognition purpose, the techniques that have been experimented are the Freeman chain codes (FCC), template matching and a proposed technique; the Freeman chain codes with characters’ features (FCCwF). The results from the experiment shows that the proposed segmentation technique; the connected component labeling with minimum object removal able to increase the segmentation success rate by more than 96% and the proposed recognition technique; the Freeman chain codes with characters’ features is able to reach the accuracy rate of 95% compared to other tested techniques. Based on the experiments and results, Freeman chain codes are efficient and accurate enough to recognize various font types of Malaysian car plates for most of the characters with less processing time of 0.1s but a higher recognition accuracy rate can be gained by combining FCC with characters’ features.

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings ( 2 )
Title notes ( 3 )

Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Thesis	UMPLIB GAMBANG	TA1637 .A45 2011 rs Thesis (Browse shelf(Opens below))	1	Not for loan		0000063467
Thesis	UMPLIB GAMBANG	CD 5997 \| TA1637 .A45 2011 rs Thesis (Browse shelf(Opens below))	1	Not for loan		0000063468

Thesis (Master of Science (Computer)) -- Universiti Malaysia Pahang - 2011

Bibliography : p. 90-96

Research on automatic car plate recognition has been widely and intensively conducted all over the world with the application of various types of segmentation and recognition techniques by researchers. Most of the recognition techniques applied are not focusing on shape-based recognition although through normal human vision, each character in the car plate has a unique and different shape with each other. The chosen techniques have contributed into many proposed suitable methodologies for car plate recognition research but with the same objectives; to gain high or increase the segmentation and recognition accuracy rate with less processing time. This research is conducted with the aim of identifying the suitable or appropriate segmentation technique which can be used to segment either the standard or non-standard specification car plates. Besides that, the objective is also to study whether the shape-based recognition technique is efficient and accurate enough to recognize Malaysian car plates which are varied in terms of font types. Techniques that have been chosen for segmentation process are pixel count, connected component labeling (CCL) and a proposed technique; the connected component labeling with minimum object removal. As for recognition purpose, the techniques that have been experimented are the Freeman chain codes (FCC), template matching and a proposed technique; the Freeman chain codes with characters’ features (FCCwF). The results from the experiment shows that the proposed segmentation technique; the connected component labeling with minimum object removal able to increase the segmentation success rate by more than 96% and the proposed recognition technique; the Freeman chain codes with characters’ features is able to reach the accuracy rate of 95% compared to other tested techniques. Based on the experiments and results, Freeman chain codes are efficient and accurate enough to recognize various font types of Malaysian car plates for most of the characters with less processing time of 0.1s but a higher recognition accuracy rate can be gained by combining FCC with characters’ features.