Integrated image segmentation-based solution for object collision detection in 2d simulation environments

Abstract

Collision detection plays a pivotal role in various fields, including robotics, virtual reality, medical simulation, and autonomous systems, where accurate modeling of object interactions is essential. This study investigates image segmentation-based methods for object collision detection in 2D simulation environments, focusing on three key algorithms: the Watershed algorithm, Active Contour Snake model, and Chan-Vese model. Through the analysis of six simulated video datasets featuring varying object properties and motion complexities, the research evaluates these algorithms based on execution time, segmentation accuracy, and adaptability to dynamic backgrounds and overlapping objects. Key findings reveal that each algorithm exhibits distinct advantages and limitations. The Watershed algorithm effectively separates overlapping objects but requires marker-based preprocessing to mitigate over-segmentation. The Active Contour Snake model captures complex object boundaries and adapts well to shape changes but demands precise initialization and high computational resources. The Chan-Vese model excels in low-contrast and noisy environments, though its iterative optimization may hinder real-time applications. These insights underscore the trade-offs between algorithmic complexity and real-time performance. The study contributes to theoretical advancements in segmentation methods while providing practical recommendations for applications in gaming, robotics, and automation. It highlights strategies to enhance computational efficiency and accuracy, ensuring broader applicability in real-world scenarios. Limitations, such as the 2D simulation scope and computational demands, are acknowledged, with suggestions for future research to explore 3D environments, adaptive techniques, and machine learning integration to improve scalability and robustness. This research offers a foundation for further innovation in collision detection technologies