Image detection of photoelasticity effect
Photoelasticity is a property of some transparent materials to become birefringent when they are subjected to mechanical stress. When a photoelastic material is subjected to mechanical stress, it experiences birefringence, which means that it splits light passing through it into two separate rays. The resulting optical effect is known as photoelasticity.
The objective of this project is to detect the photoelasticity effect in images of photoelastic materials. The project will use image processing techniques to identify the regions of the image that show signs of photoelasticity.
The project will use the following steps to detect the photoelasticity effect in images:
- Preprocess the image to enhance the contrast and reduce noise.
- Detect the edges of the image using edge detection algorithms.
- Identify the regions of the image that show signs of photoelasticity based on the edge detection results.
- Highlight the regions of the image that exhibit the photoelasticity effect.
The project will be implemented in Python using the following libraries:
- OpenCV: For image processing and computer vision tasks.
- NumPy: For numerical computing and array operations.
- Matplotlib: For plotting and visualization of images.
The project will use a dataset of images of photoelastic materials. The dataset will contain images of photoelastic materials under different stress conditions to demonstrate the photoelasticity effect.
The project will generate visualizations of the detected photoelasticity effect in the images. The results will show the regions of the image that exhibit birefringence due to mechanical stress.
The project will demonstrate the use of image processing techniques to detect the photoelasticity effect in images of photoelastic materials. The results will help visualize and analyze the photoelasticity effect in transparent materials.