Object detection using image processing techniques: coconut as a case study

The use of computers to analyze images has many potential but, the variability of the objects makes it a challenging task. In this thesis, the main idea is to detect an object (coconut) from an image. Several techniques have been utilized namely, the separable filter, Circular Hough Transform (CH...

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Main Author:	Haniza, Yazid
Format:	Thesis
Language:	English
Subjects:	Object detection Image processing Filter Circular Hough Transform (CHT)
Online Access:	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/63410/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/63410/2/Full%20text.pdf
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id	my-unimap-63410
record_format	uketd_dc
spelling	my-unimap-634102019-11-24T08:30:38Z Object detection using image processing techniques: coconut as a case study Haniza, Yazid Assoc. Prof. Dr. Mohd Rizon Mohd Juhari The use of computers to analyze images has many potential but, the variability of the objects makes it a challenging task. In this thesis, the main idea is to detect an object (coconut) from an image. Several techniques have been utilized namely, the separable filter, Circular Hough Transform (CHT), chord intersection and moment invariant. Before applying these techniques, the preprocessing and image segmentation steps need to be performed in priori. Histogram equalization is utilized in preprocessing step meanwhile edge detection and morphological filtering have been employed in image segmentation step. Single object has been experimented to evaluate the two (2) techniques, CHT and the chord intersection. Based on the results obtained from single object detection, the CRT achieves higher percentage, 87.5% than chord intersection technique, 85%. For multiple objects detection, the CHT technique has been used and the highest detection for the first object is 87.5% followed by 92.5% for the second object, 77.5% for the third object and the last object is 67.5%. The moment invariant technique has been used to extract the shape of the object and detect its presence. From 50 images that have been experimented, 90% show positive result. This research can be adopted for climbing robotic system that can automatically pluck the coconut from a tree. Using image processing techniques, the gripping process will be easier and convenient than manual plucking. Kolej Universiti Kejuruteraan Utara Malaysia (KUKUM) 2007 Thesis en http://dspace.unimap.edu.my:80/xmlui/handle/123456789/63410 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/63410/1/Page%201-24.pdf a2352d0298d3aa5753214842b0dc4ab9 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/63410/2/Full%20text.pdf 51c3ae2d97fbafdbeb6f89c097c8f207 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/63410/3/license.txt 8a4605be74aa9ea9d79846c1fba20a33 Object detection Image processing Filter Circular Hough Transform (CHT) School of Computer and Communication Engineering
institution	Universiti Malaysia Perlis
collection	UniMAP Institutional Repository
language	English
advisor	Assoc. Prof. Dr. Mohd Rizon Mohd Juhari
topic	Object detection Image processing Filter Circular Hough Transform (CHT)
spellingShingle	Object detection Image processing Filter Circular Hough Transform (CHT) Haniza, Yazid Object detection using image processing techniques: coconut as a case study
description	The use of computers to analyze images has many potential but, the variability of the objects makes it a challenging task. In this thesis, the main idea is to detect an object (coconut) from an image. Several techniques have been utilized namely, the separable filter, Circular Hough Transform (CHT), chord intersection and moment invariant. Before applying these techniques, the preprocessing and image segmentation steps need to be performed in priori. Histogram equalization is utilized in preprocessing step meanwhile edge detection and morphological filtering have been employed in image segmentation step. Single object has been experimented to evaluate the two (2) techniques, CHT and the chord intersection. Based on the results obtained from single object detection, the CRT achieves higher percentage, 87.5% than chord intersection technique, 85%. For multiple objects detection, the CHT technique has been used and the highest detection for the first object is 87.5% followed by 92.5% for the second object, 77.5% for the third object and the last object is 67.5%. The moment invariant technique has been used to extract the shape of the object and detect its presence. From 50 images that have been experimented, 90% show positive result. This research can be adopted for climbing robotic system that can automatically pluck the coconut from a tree. Using image processing techniques, the gripping process will be easier and convenient than manual plucking.
format	Thesis
author	Haniza, Yazid
author_facet	Haniza, Yazid
author_sort	Haniza, Yazid
title	Object detection using image processing techniques: coconut as a case study
title_short	Object detection using image processing techniques: coconut as a case study
title_full	Object detection using image processing techniques: coconut as a case study
title_fullStr	Object detection using image processing techniques: coconut as a case study
title_full_unstemmed	Object detection using image processing techniques: coconut as a case study
title_sort	object detection using image processing techniques: coconut as a case study
granting_institution	Kolej Universiti Kejuruteraan Utara Malaysia (KUKUM)
granting_department	School of Computer and Communication Engineering
url	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/63410/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/63410/2/Full%20text.pdf
_version_	1747836855727947776

Object detection using image processing techniques: coconut as a case study

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