Efficient Superpixel Creation in High-resolution Images by Applying a PLANT
Autonomous robots attempt to understand their environment in real-time. The data structure PLANT, which this thesis introduces, segments large amounts of data efficiently. To detect homogeneous image regions fast, a PLANT combines an integral image with a binary search. Beyond that, a PLANT-based vision for soccer-playing robots is presented. It enables the robots to perceive their environment with a camera resolution of 1920×1080 pixels at a frame rate of 30 Hz. For superpixel creation, the algorithms _PLANT and _PLANTm are introduced. The time complexities of _PLANT and _PLANTm are O(n + k·log(n)) and O(n + k·log(n) + k^^2), where n is the number of pixels and k the number of superpixels. PLANT-based algorithms benefit from the spatial locality of reference, which results in a high speed-up.