Counting and Classification of Flies on Yellow sticky traps

Python OpenCV Matplotlib Numpy Git Image Processing

Counting and classification of insects on yellow fly traps using image processing techniques.

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Feature image

In agricultural research, the manual task of counting and categorizing insects on yellow sticky traps has long been known for its challenges, including time consumption and potential errors.

In this project, an innovative solution is proposed based on image processing techniques. This method involves several steps,

  1. Image enhancement
  2. Removal of unwanted elements
  3. Classification based on color information (HSV Seperation based)

(Entire work done based on pure image processing techniques wihout using Deep Learning)

The main objective of this approach would be the automated classification and counting of three insect types: Whitefly, Macrolophus, and Nesidiocoris.

The results demonstrate improvements in efficiency and accuracy compared to manual counting methods. Moreover, this system could be integrated into data analysis workflows, enabling timely monitoring and decision support in agricultural contexts.

This solution emphasizes the potential of image processing as a practical and resource-efficient tool, with promising implications for entomological research and agricultural pest management.