MATLAB Implementation of Active Shape Models for Image Processing and Pattern Recognition

In this document, I will present detailed information about implementing Active Shape Models (ASM) using MATLAB code. ASM represents a sophisticated technique widely employed in image processing and pattern recognition domains. The implementation enables precise localization and analysis of specific shapes or patterns within digital images. Through MATLAB's ASM implementation, users can automatically extract regions of interest from images for subsequent analysis and processing. The code typically involves key components such as point distribution models, profile modeling, and iterative shape fitting algorithms using eigenvalue decomposition and Mahalanobis distance calculations. This methodology proves particularly valuable in medical image analysis, computer vision systems, and facial recognition applications. Understanding the MATLAB implementation of ASM code empowers developers to effectively leverage this robust technique through functions handling shape initialization, gray-level profile extraction, and constrained shape deformation processes.