MARC details
| 000 -LEADER |
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| fixed length control field |
03142nam a2200265 a 4500 |
| 001 - CONTROL NUMBER |
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| control field |
vtls000058750 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
KUKTEM |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20251114204513.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
120321t2011 my a f m 000 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
THE0002939(Local) |
| 039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE] |
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| Level of rules in bibliographic description |
201905140825 |
| Level of effort used to assign nonsubject heading access points |
zul |
| Level of effort used to assign subject headings |
201203211116 |
| Level of effort used to assign classification |
ida |
| -- |
201203211004 |
| -- |
ida |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
UMP |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
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| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
TA1637 .A45 2011 rs Thesis |
| 100 0# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Nor Amizam Jusoh |
| 245 10 - TITLE STATEMENT |
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| Title |
Segmentation and recognition of Malaysian car plates using Freeman chain codes / |
| Statement of responsibility, etc. |
Nor Amizam Jusoh |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
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| Place of publication, distribution, etc. |
Kuantan, Pahang : |
| Name of publisher, distributor, etc. |
UMP, |
| Date of publication, distribution, etc. |
2011 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xiv, 105 p. : |
| Other physical details |
ill. (some col.) ; |
| Dimensions |
30 cm. + |
| Accompanying material |
1 CD-ROM |
| 502 ## - DISSERTATION NOTE |
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| Dissertation note |
Thesis (Master of Science (Computer)) -- Universiti Malaysia Pahang - 2011 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc. note |
Bibliography : p. 90-96 |
| 520 3# - SUMMARY, ETC. |
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| Summary, etc. |
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. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Image processing |
| General subdivision |
Digital techniques |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Optical pattern recognition |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Computer vision |