Gaussian Mixture Model MATLAB Implementation
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Resource Overview
Detailed Documentation
Gaussian Mixture Modeling (GMM) is a widely-used image processing technique applicable to image segmentation, object detection, and related computer vision tasks. This implementation utilizes the Expectation-Maximization (EM) algorithm to estimate Gaussian component parameters, providing probabilistic clustering capabilities. Our MATLAB version includes optimized parameter initialization and convergence checking mechanisms to ensure computational efficiency. The code features comprehensive error handling and supports customizable Gaussian component numbers for different application scenarios. We guarantee this implementation's correctness through rigorous testing with standard datasets. If you require this tool, please download it from the link below. We sincerely appreciate your support and welcome feedback for further improvements.
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