Difference between revisions of "Image Processing for Plant Detection"

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= Description =
 
= Description =
   
In a research cooperation of SCC with da-cons, we are investigating
+
In a research cooperation of SCC with da-cons, we are investigating methods and algorithms to detect a plant on a photograph. The overall aim is to calulate, e.g., the age or condition of the plant. Derived from this, we offer an enclosed task for students to detect if the pixel of an image is part of a plant or not.
methods and algorithms to
 
detect a plant on a photograph. The overall aim is to calulate, e.g.,
 
the age or
 
condition of the plant. Derived from this, we offer an enclosed task for
 
students to detect
 
if the pixel of an image is part of a plant or not.
 
   
 
= Tasks =
 
= Tasks =
  +
To achieve the described goals, you need to setup a toolchain first to exclude as many irrelvant information as possible from the given images. After identifying the plants in the bed, you need to develop a filter to only recognize the pixels of the plants in it. Note, that the angle of the image might change, i.e., your method needs to be robust and able to cope with such images. As an extension, we also have images that were shot with an infrared camera during the night which make the distinction more complex. After implementing your approach, you need to evaluate and write a documentation (including theoretical aspects and your approach, ~ x pages) about it.
To achieve the described goals, you need to setup a toolchain first to
 
exclude as many irrelvant information
 
as possible from the given images. After identifying the plants in the
 
bed, you need to develop a filter to only
 
recognize the pixels of the plants in it. Note, that the angle of the
 
image might change, i.e., your method needs to
 
be robust and able to cope with such images. As an extension, we also
 
have images that were shot with an infrared camera during the night
 
which make the distinction more complex. After implementing your
 
approach, you need to evaluate and write a documentation
 
(including theoretical aspects and your approach, ~ x pages) about it.
 
   
After the project has finished, you also have to give a presentation (~
+
After the project has finished, you also have to give a presentation (~ 30 mins) about your achievements.
x mins) about your achievements.
 
   
   
 
= Requirements =
 
= Requirements =
 
* familiarity with C/C++
 
* familiarity with C/C++
* knowlegde/understanding of image processing, ideally experience with
+
* knowlegde/understanding of image processing, ideally experience with an image processing library, e.g., OpenCV
an image processing library, e.g., OpenCV
 
   
   

Revision as of 19:13, 12 September 2016

Description

In a research cooperation of SCC with da-cons, we are investigating methods and algorithms to detect a plant on a photograph. The overall aim is to calulate, e.g., the age or condition of the plant. Derived from this, we offer an enclosed task for students to detect if the pixel of an image is part of a plant or not.

Tasks

To achieve the described goals, you need to setup a toolchain first to exclude as many irrelvant information as possible from the given images. After identifying the plants in the bed, you need to develop a filter to only recognize the pixels of the plants in it. Note, that the angle of the image might change, i.e., your method needs to be robust and able to cope with such images. As an extension, we also have images that were shot with an infrared camera during the night which make the distinction more complex. After implementing your approach, you need to evaluate and write a documentation (including theoretical aspects and your approach, ~ x pages) about it.

After the project has finished, you also have to give a presentation (~ 30 mins) about your achievements.


Requirements

  • familiarity with C/C++
  • knowlegde/understanding of image processing, ideally experience with an image processing library, e.g., OpenCV


References

[0] [- http://opencv.org/ opencv]

Contact

Christoph.Koenig@kit.edu