a fuzzy logic approach for improved houck tranform to

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A FUZZY LOGIC APPROACH FOR IMPROVED HOUCK TRANFORM TO EXTRACT CADASTRAL SYMBOL FROM MALAYSIAN CADASTRAL MAP

CHAI TED SING

A thesis submitted

in full fulfillment of the requirem& for the degree of Master of Science in Information Technology

FACULTY OF INFORMATION TECHNOLOGY UNIVERSITI MALAYSIA SARAWAK

2002

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Figure 4.17:

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Figure 5.1:

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Figure 5.11

Sample of the fuzzy rule created using the Rule Editor of Fuzzy Logic

toolbox . . . .70 Load centroids from text file and plot them as circle symbol on the input mage ,,,,,,,,,.,...,...,,,,,,,,.,,... 72 Sample input images used for the initial experiments. MaplA and Map2A were derived from Map1 and Map2 respectively, by removing all the

noises (lines and text labels). ,,,,,,...._....,,,,,,,,,,....,,,.,... 74 Effect of radius on the maximum accumulated votes in parameter space of the standard Hough Transform. . . ..__...,,,,,,,,..,,,..,... 75 Comparison chart showing the parcel corner detection rates obtained by using different peak threshold for the standard Hough transform 76 Effect of radius of computation on signal-intensity extraction. .._____... 78 Effect of angular sampling interval on signal-intensity extraction. . . ...79 Effect of radial sampling interval on signal-intensity extraction ,... 80 The original position (Set I) and shifted positions (Set lA, Set IB, Set

lC, and Set 1D) of the signal-intensity membership functions 82 Comparison chart showing the parcel comer detection rates obtained by using the original and shifted positions of signal-intensity membership functions in the Fuzzy Expert System . . . 83 The original position (Set 2) and shifted positions (Set 2A, Set 2B, Set 2C, and Set 2D) of the noise-intensity membership function. 84 Comparison chart showing the parcel corner detection rates obtained by using the original and shifted positions of noise-intensity membership

functions in the Fuzzy Expert System .,,...,,,,,,,,,,,,... 85 The original position (Set 3) and shifted positions (Set 3A, Set 3B, Set 3C, 3D and Set 3E) of the roundness membership function. 86 Figure 5.12: Comparison chart showing the parcel corner detection rates obtained by

using the original and shifted positions of the’roundness membership

functions in the Fuzzy Expert System ..,...,,,, c,: ,,,,,.,,,... 87 Figure 5.13: Comparison chart showing the parcel comer detection rates obtained by

using different Perfectness threshold for the true carper detection...88 Figure 5.14 Input images (Mapl, Map2. Map3 and Map4) used for the evaluation of

the developed prototype . . . 90 Figure 5.15 Input image (Map5) used for the evaluation of the developed prototype . . . ...91 Figure 5.16: Composite Images (reduced) of Mapl showing the result of parcel comer

detection using

a) Standard Hough transform

b) Developed prototype ..,,,,_.,,,,,,,,,,,,,,,,,,,.,...,.,,,,,,,,,,,,,,,,... 93

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