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02631nam a22002417a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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ft8881 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20251215155147.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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251215b ||||| |||| 00| 0 eng d |
| 041 ## - LANGUAGE CODE |
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| Language code of text/sound track or separate title |
engtag |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
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| Classification number |
QA76.9 A43 D68 2025 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
. |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Doton, Ronald R., Jr.; Escober, Rainier J. |
| 245 ## - TITLE STATEMENT |
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| Title |
Enhancement of circle hough transform to be applied in circular road traffic sign recognition |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
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| Place of production, publication, distribution, manufacture |
. |
| Name of producer, publisher, distributor, manufacturer |
. |
| Date of production, publication, distribution, manufacture, or copyright notice |
c2025 |
| 300 ## - PHYSICAL DESCRIPTION |
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Undergraduate Thesis: (Bachelor of Science in Computer Science) - Pamantasan ng Lungsod ng Maynila, 2025 |
| 336 ## - CONTENT TYPE |
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text |
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text |
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text |
| 337 ## - MEDIA TYPE |
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unmediated |
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unmediated |
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unmediated |
| 338 ## - CARRIER TYPE |
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volume |
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volume |
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volume |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
ABSTRACT: The Enhanced Circle Hough Transform (ECHT) is an optimized algorithm designed to improve the accuracy and efficiency of circular object detection in digital images. This study focuses on minimizing computational load while enhancing detection precision and reliability. ECHT incorporates three core enhancements: the Kasa method for exact mathematical circle fitting, Contrast Limited Adaptive Histogram Equalization (CLAHE) for refining potential circle center locations by improving local contrast, and adaptive parameters that dynamically adjust in response to input data. These improvements eliminate the need for manual tuning, ensuring optimal performance under varying conditions and increasing overall productivity. The objective of this research are: (1) to lessen the computational complexity using mathematical equations such as the Kasa method, (2) to improve the algorithm’s capability to accurately recognize circles while minimizing false detections, and (3) to implement adaptive parameters for automatic system optimization. The methodology includes applying the Kasa method for efficient circle fitting, utilizing CLAHE to enhance image contrast and assist in identifying likely circle centers, and integrating adaptive parameters to allow real-time adjustments based on image variability. Performance evaluations demonstrate ECHT’s superiority over the traditional Circle Hough Transform (CHT). ECHT achieves higher precision (81% vs. 29%), greater F1-score (75% vs. 33%) and faster execution time (0.3113 sec vs. 0.4464 sec). Although CHT reports a slightly higher recall (84% vs 75%), it results in more false positives, lowering overall detection reliability. ECHT, by contrast, offers a better balance of precision and recall, making it a more robust and computationally efficient solution for practical circle detection tasks. |
| 526 ## - STUDY PROGRAM INFORMATION NOTE |
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| Classification |
Filipiniana |
| 655 ## - INDEX TERM--GENRE/FORM |
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| Genre/form data or focus term |
academic writing |
| 942 ## - ADDED ENTRY ELEMENTS |
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| Source of classification or shelving scheme |
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| Item type |
Thesis/Dissertation |