Region of Interest Image Processing
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Resource Overview
A Python and OpenCV implementation for selecting and processing regions of interest (ROI) from images in formats like JPG and TIFF. Includes interactive ROI selection, display functionality, and post-processing operations with algorithm explanations and code structure details.
Detailed Documentation
This implementation provides functionality to select regions of interest in images supporting various formats including JPG and TIFF. The core algorithm utilizes OpenCV's mouse callback functions for interactive ROI selection, where users can click and drag to define rectangular regions. The code employs cv2.selectROI() function for coordinate extraction and cv2.imshow() for real-time display of selected regions.
For post-processing operations, the implementation includes:
- Cropping using array slicing: roi_cropped = image[y:y+h, x:x+w]
- Rotation transformation through affine transformation matrices
- Filter application using OpenCV's filter2D() function with customizable kernels
The system architecture follows a modular approach with separate functions for ROI selection, display, and processing operations. Error handling includes format validation using file extension checks and exception handling for invalid ROI coordinates. This approach enables efficient image analysis by extracting relevant portions for detailed examination and further computational processing.
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