DIGITAL IMAGE PROCESSING IN AGRICULTURAL TECHNOLOGIES
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Course Title:
DIGITAL IMAGE PROCESSING IN AGRICULTURAL TECHNOLOGIES
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Course Code:
BSM5049
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Type of Course:
Optional
4
Level of Course:
Second Cycle
5
Year of Study:
1
6
Semester:
1
7
ECTS Credits Allocated:
6
8
Theoretical (hour/week):
3
9
Practice (hour/week) :
0
10
Laboratory (hour/week) :
0
11
Prerequisites:
None
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Recommended optional programme components:
None
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Language:
Turkish
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Mode of Delivery:
Face to face
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Course Coordinator:
Doç. Dr. FERHAT KURTULMUŞ
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Course Lecturers:
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Contactinformation of the Course Coordinator:
ferhatk@uludag.edu.tr Ziraat Fakültesi, Biyosistem Mühendisliği Bölümü, C Blok 2. Kat
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Website:
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Objective of the Course:
Matlab program, which is a software package for industrial and research purposes for data analysis, visualization and technical calculations, helps students to understand the advantages of using digital image processing technologies in agricultural production, to use data types, algorithms, transformations and basic methods used in digital image processing, to be able to utilize image processing tools as a solution to the problems encountered in agricultural production.
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Contribution of the Course to Professional Development
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Learning Outcomes:
1
be able to use Matlab and image processing tools at the basic level.;
2
Recognizing the tools and methods currently used in the field of digital image processing.;
3
be able to understand basic image processing algorithms and how to apply them.;
4
be able to design digital image processing methods as a sensor system that can be used in agricultural production.;
5
be able to understand the current and future technology requirements of digital image processing in the field of agriculture.;
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Course Content:
Week
Theoretical
Practical
1
Introduction to digital image processing, definitions, concepts, visible and invisible wave length, human vision system
2
Matlab working environment and basic image IO functions
3
Basic data types in digital image processing
4
Gray level transformations, histogram equalization and some image enhancement methods
Feature extraction methods for image objects, color, shape, and textures
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Frequency components and Fourier transform of digital images
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Image segmentation and object recognition
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Object recognition-counting and Matlab sample work
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Image processing in precision agriculture and Matlab sample work
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Detection of agricultural material by digital image processing
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Image processing applications to classify agricultural products
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Textbooks, References and/or Other Materials:
Gonzalez, R.C., Woods, R.E., Eddins, S.L., Digital Image Processing Using MATLAB, Prentice-Hall, 2003. Palm, W.J., Introduction to Matlab 7 for Engineers, McGraw Hill, 2005.
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Assesment
TERM LEARNING ACTIVITIES
NUMBER
PERCENT
Midterm Exam
1
40
Quiz
0
0
Homeworks, Performances
0
0
Final Exam
1
60
Total
2
100
Contribution of Term (Year) Learning Activities to Success Grade
40
Contribution of Final Exam to Success Grade
60
Total
100
Measurement and Evaluation Techniques Used in the Course
Information
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ECTS / WORK LOAD TABLE
Activites
NUMBER
TIME [Hour]
Total WorkLoad [Hour]
Theoretical
14
3
42
Practicals/Labs
0
0
0
Self Study and Preparation
14
3
42
Homeworks, Performances
0
10
60
Projects
0
0
0
Field Studies
0
0
0
Midtermexams
1
20
20
Others
0
0
0
Final Exams
1
16
16
Total WorkLoad
180
Total workload/ 30 hr
6
ECTS Credit of the Course
6
26
CONTRIBUTION OF LEARNING OUTCOMES TO PROGRAMME QUALIFICATIONS
