Hough Transform Based Iris Detection and Localization Method
- Login to Download
- 1 Credits
Resource Overview
Detailed Documentation
This technology enables robust facial recognition and precise eye position detection. It employs machine learning algorithms and deep neural networks to analyze facial contours and distinctive features for identification. The implementation typically involves computer vision techniques such as edge detection, contour analysis, and Hough transform for accurate iris localization. Key functions include preprocessing images through Gaussian filtering, applying Canny edge detection to highlight ocular boundaries, and utilizing circular Hough transforms to detect iris patterns. This technology finds extensive applications in security surveillance systems, facial authentication platforms, and smart home devices. Furthermore, through continuous training with expanded datasets and optimization of convolutional neural network (CNN) architectures, the system can progressively enhance detection accuracy, achieving greater intelligence and precision in real-world scenarios.
- Login to Download
- 1 Credits