03142nam a2200265 a 4500 vtls000058750 KUKTEM 20251114204513.0 120321t2011 my a f m 000 0 eng d THE0002939(Local) 201905140825 zul 201203211116 ida 201203211004 ida UMP TA1637 .A45 2011 rs Thesis Nor Amizam Jusoh Segmentation and recognition of Malaysian car plates using Freeman chain codes / Nor Amizam Jusoh Kuantan, Pahang : UMP, 2011 xiv, 105 p. : ill. (some col.) ; 30 cm. + 1 CD-ROM 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. Image processing Digital techniques Optical pattern recognition Computer vision 0 0 lcc 0 1 10000 10000 2019-09-04 0 TA1637 .A45 2011 rs Thesis 0000063467 2019-09-04 00:00:00 1 2019-09-04 THESIS 0 0 lcc 0 1 10000 10000 2019-09-04 0 CD 5997 | TA1637 .A45 2011 rs Thesis 0000063468 2019-09-04 00:00:00 1 2019-09-04 THESIS VIRTUA40 3164 3170 VTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*6502*9992