Eisha-Tir-Razia Seminar UAF

1. Seminar
Application of Fourier Transform
in Agriculture

2. Agriculture
• Agriculture plays one of the most
important roles in economy.
• Therefore, lowering costs and
improving quality of agricultural
products is highly demanded.

3. One of the Most Important and Expensive
Labor
• Controlling Weeds
through
Hand/Human labor
oCostly
oTime consuming
Herbicides
oCostly
oPollution causing

4. A Weed
• Every plant which has
grown in an inappropriate
place.
• For example, Amaranth
is a weed if it is grown in
corn crop.

5. Alternative to Hand Labor and
Herbicides
• Robotic
Cultivators
Armed with
Digital
Camera

6. Basic Target of Robotic Cultivator
• Instantaneous weed detection and
removal
o Weed detection
by
classifying between weeds and crops
based on captured image
o Weed removal
by
spraying herbicide accurately on the weed
cutting with blades
damaging with electric shock devices

7. How Robotic Cultivators Work?
• It has digital camera fitted in it.
• Camera captures images of weed
and crop.
• Classify between weed and crop
using those images.
• If it is of weed then robot removes it
otherwise it leaves the crop.

8. Techniques Used for Weeds
Detection
• Robotic weed control system for tomatoes
• Computer vision based methods for
detecting weeds in lawns
• Fourier Transform-Computers

9. Fourier Transform
• Fourier Transform:
converts a function from the time domain
to the frequency domain

10. Forward Fourier Transform
• From time domain to frequency domain
f(u,v) t
t(x,y)
kernel

11. Inverse Fourier Transform
• From frequency domain to time domain
t(x,y) f
kernel

12. Transform Kernel

14. Basic Process for Weed Detection
• Pre-Processing (Edge Detection)
• Frequency and Density Filtering
(Fourier Transform in Frequency Filtering)
• Post-Processing (Classification errors
are detected, merging results of both
frequency and density filters)

15. Phase of Frequency Filtering
• Image of plant (weed/crop) after edge
detection is gone through frequency
filtering.
• A grid is applied on that image, on each
block of grid, Fourier transform is
applied.
• The output will be in frequency domain,
which will be provided to computational
area of robotic cultivator.

16. Further Process
• Density Filtering
• Post-Processing
– Detection of classification errors
– Merging the results of both frequency filtering
(which is done using Fourier Transform) and
density filters.

17. Output
Resulting output will be a matrix
(Weed Location)

18. Application Compiled to DLL
• The resulting application after being
computed to Dynamic Linked Library (dll)
used in a Graphical User Interface (GUI)
– May be in C#.NET based GUI

19. Overview

20. Experiment
• An experiment was done, in which this
algorithm was used in a weeding robot
built in Mechanical Department of Shiraz
University in Iran, for being tested in an
actual corn field.
• Results showed more than 92% accuracy
in detecting weed plants.

21. Thank You!