مشخصات پژوهش

عنوان	An Improved Snake Model for Extraction Automatically of Buildings from Urban Aerial Images and LiDAR Data
نوع پژوهش	مقاله ارائه شده کنفرانسی
کلیدواژه‌ها	Building Extraction, Snake Model, LiDAR Data
چکیده	The automatic extraction of objects from laser scanners data and images has been a topic of research for decades. This paper proposes an improved snake model focusing on building extraction from color aerial images and LiDAR data. A snake is defined as an energy minimizing spline guided by external constraint forces and influenced by image forces that pull it toward features such as lines or edges. Based on the radiometric and geometric behaviors of buildings, the snake model is modified in two aspects: the criteria for the selection of initial seeds and the external energy function. The proposed snake model associated with new height similarity factor energy and regional similarity energy as well as Gradient Vector Flow (GVF) to attract the snake approaching the object contours efficiently. Compared with traditional snake model, this algorithm can converge to the true building contours quicker and stable from complex environment.
پژوهشگران	سلمان احمدی (نفر سوم)، حمید عبادی (نفر دوم)، مصطفی کابلی زاده (نفر اول)