A Software System for Processing Images with Parallel Computing

Abstract

In this paper, a software system for image processing with parallel computing based on the geometrized histograms method developed for the concise description and segmentation of color images and for designing real-time image understanding systems is described. The parallel processing leans on the fact that, in contrast to the majority of the existing image segmentation methods, the proposed method is designed so that the most labor-consuming operations with the pixel array can be executed using n independent threads. The principles of designing programs for data processing in separate threads in which the program produces a substantial, compressed description of an image (a frame of a video sequence) that preserves the geometrical relations of the source image but has a dimension by several orders of magnitude less than the original image are described. The main operations of the segmentation and image understanding systems are executed without using the image pixel array—only using the designed concise description. These operations require a short execution time (on the average less than 10 ms for the whole set of tasks) on standard modern personal computers, even for HD video. In this paper, a multithreaded implementation of constructing a concise description of an image (a frame) is considered that allows one to enhance the operation speed, which is already fairly high, up to the record productivity figures. The application to systems for understanding road scenes, such as systems for finding the road region, its roadsides, the sky region, to systems for detecting and understanding road markings (permanent white and temporary colored), as well as to finding signal lamps of helicopters, are also described. Examples of processing results for particular road scenes are presented and discussed, and estimates of the operation speed for video sequences of real road scenes are given.