https://github.com/ahmedabdalkreem/connected_component_labeling

Technique used to detect small object in the image like shapes and number can used this technique in OCR.
https://github.com/ahmedabdalkreem/connected_component_labeling

computer-vision connected-components matplotlib numpy object-detection python rgb2gray threshold

Last synced: about 21 hours ago
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Technique used to detect small object in the image like shapes and number can used this technique in OCR.

• Host: GitHub
• URL: https://github.com/ahmedabdalkreem/connected_component_labeling
• Owner: AhmedAbdAlkreem
• Created: 2023-08-21T18:03:36.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2023-08-29T19:10:26.000Z (about 1 year ago)
• Last Synced: 2024-01-26T11:11:07.843Z (10 months ago)
• Topics: computer-vision, connected-components, matplotlib, numpy, object-detection, python, rgb2gray, threshold
• Language: Jupyter Notebook
• Homepage:
• Size: 4.75 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Connected_Component_Labeling

Technique used to detect small object in the image like shapes and number can used this technique in OCR.

# What is the mean of connected component labeling?

Technique used when need to detect object from image but this is simple technique not advanced technique 

know to detect any objects in image very clear and this technique used to detect small things like number

in image, shapes or things has speacific area.

# What you will learn before this project?

1) To read image and tranform from rgb to gray.

2) Make threshold in image to be binary.

3) Using open-CV library.

4) Call connected_component from cv2.

5) Detect all shapes from the image.

6) Detect all number from sudoku image.

7) Deal with noise from the image to detect object only.

Before this you will be able to detect all object from the image without noise and I hope

to add more details in connected component labeling about you know.