Gürel, Cahit

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Profile URL
https://hdl.handle.net/20.500.14411/7823
Name Variants
C., Gurel
G., Cahit
Gürel, Cahit
Gürel,C.
C.,Gürel
Gurel,C.
Cahit, Gürel
C.,Gurel
G.,Cahit
Cahit, Gurel
Gurel, Cahit
Job Title
Öğretim Görevlisi
Email Address
cahit.gurel@atilim.edu.tr
Main Affiliation
Department of Mechatronics Engineering
Status
Former Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID

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Scholarly Output

6

Articles

0

Views / Downloads

11/16

Supervised MSc Theses

1

Supervised PhD Theses

1

WoS Citation Count

0

Scopus Citation Count

4

Patents

0

Projects

0

WoS Citations per Publication

0.00

Scopus Citations per Publication

0.67

Open Access Source

0

Supervised Theses

2

JournalCount
20th Annual International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2013 -- 20th Annual International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2013 -- 20 September 2013 through 20 September 2013 -- Ankara -- 1022763
21st Mechatronics and Machine Vision in Practice, M2VIP 2015 -- 21st Mechatronics and Machine Vision in Practice, M2VIP 2015 -- 7 July 2015 through 9 July 2015 -- Manila -- 1194561
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2013 - 20153
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Scholarly Output Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 4
    Conceptual Design of a Rose Harvesting Robot for Greenhouses
    (2013) Gürel,C.; Erden,A.
    Agricultural applications has made over thousands years, and the entire processes dependent to people. The dependency increases the labor time of the process and as well as cost of the products. To overcome this problem, the automated systems on the agricultural processes are needed in the place of humans. Many implementations are made on the harvesting processes in different products, i.e., rose, apple, cherry, strawberry, etc. which shows the importance of automation in the harvesting. The company needs a system that makes harvesting of the roses instead of human in greenhouse. Conceptual design of rose harvesting robot is given in this paper which is covers need, intended users, functions and top level intelligence algorithm.
  • Thumbnail Image
    Conference Object
    Face Detection Algorithm With Facial Feature Extraction for Face Recognition System
    (Mechatronics and Machine Vision in Practice, 2013) Gürel,C.; Erden,A.
    A face recognition system is one of the biometric information processes, its applicability is easier and working range is wider than other systems like; fingerprint, iris scanning, signature, etc. The detection methods are designed to extract features of face region out of a digital image. The output face image of the detection algorithm should be similar to the recognition input image. Face detection is performed on live acquired images without any application field in mind. The developed system uses white balance correction, skin like region segmentation, facial feature extraction and face image extraction on a face candidate. System is also capable of detecting multiple faces in live acquired images.
  • Thumbnail Image
    Conference Object
    Rose Stem Branch Point Detection and Cutting Point Location for Rose Harvesting Robot
    (Mechatronics and Machine Vision in Practice, 2015) Gürel,C.; Hassan,M.; Zadeh,G.; Erden,A.
    The primary objective of the study is to develop a method that can locate the proper location of cutting point of rose stem for robotic rose harvesting. Stem tracking and cutting operation are achieved using with the help of stereo vision techniques. The cutting point has a vital importance for cut rose harvesting in greenhouse which affects the efficiency of new shoot from the cut stem. In agricultural process, the cutting point depends on thickness of stem and eye on stem. Locating the eye is difficult by image processing thus another relation for cut point estimation was performed. The relation between thickness and cut length can lead to relation for cut point estimation. 239 data is collected from a greenhouse and linear relation with some deviation was acquired. To perform this relation, branch point location algorithm was developed. The proposed algorithm has three steps: branch point detection; thickness calculation; and cutting length estimation. The algorithm for branch detection performs quite well to detect and locate the position of the point when there occur no overlapping. The results of branch point detection are adequate for implementing to the robot. © 2015, Mechatronics and Machine Vision in Practice. All rights reserved.