https://github.com/wadaboa/cv-con-rod-inspection
Visual inspection of motorcycle connecting rods for Computer Vision class at UNIBO
https://github.com/wadaboa/cv-con-rod-inspection
blob-analysis computer-vision euler-number motorcycle-connecting-rods
Last synced: about 2 months ago
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Visual inspection of motorcycle connecting rods for Computer Vision class at UNIBO
- Host: GitHub
- URL: https://github.com/wadaboa/cv-con-rod-inspection
- Owner: Wadaboa
- License: mit
- Created: 2020-02-14T12:58:22.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2020-02-19T16:13:33.000Z (about 5 years ago)
- Last Synced: 2025-01-20T10:23:08.057Z (3 months ago)
- Topics: blob-analysis, computer-vision, euler-number, motorcycle-connecting-rods
- Language: Python
- Size: 648 KB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Connecting rods inspection
## Description
This university project is an implementation of a visual system which is able to analyze
motorcycle connecting rods, by applying the following steps:
1. A grayscale image is loaded and binarized using `Otsu's method`
2. The image is bitwise inverted to get a white foreground and a black background
3. Morphological operations are carried out in order to detach touching rods
4. Blobs are extracted using `connected components labeling`
5. Blobs are filtered using a threshold on the blob's area, to remove iron powder and distractors
6. Circles are calculated using a custom `contour finding` method and the `Haralick's circularity` measure
7. Blob's `moments` are calculated using a custom method
8. Blob's `orientation` and its bounding box are determined
9. Blob's `shape features`, like length and width, are calculated
10. The number of holes inside each rod is computed, based on the `Euler number`
11. Finally, results are printed out
In the whole execution, images of the happening processing are shown for debug purposes.
## Dependencies
This software is written in `Python 3.7.6`, using the following third-party libraries:
* `plac 1.1.3`, to parse from CLI "the easy way"
* `scipy 1.4.1`, to efficiently perform scientific computations
* `opencv-python 4.2.0.32`, to exploit some computer vision algorithms
## Installation & execution
To install the software, just clone this repository locally.\
To execute it, `cd` into the downloaded folder (`cv-con-rod-inspection`) and run
```bash
python inspection.py -i ""
```
## Todo
The last thing to refine is how to `detach touching rods`, without altering their main structure.