Low Latency Color Segmentation on Embedded Real ... - CiteSeerX
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Low Latency Color Segmentation on Embedded Real ... - CiteSeerX
This paper presents a color segmentation algorithm for embedded real-time systems with a special ..... [1] W. Skarbek and A. Koschan, "Colour image segmentation - a survey" Tech. Rep. 94-32, ... VCIP'96, (Orlando, Florida), March 1996.
This paper presents a color segmentation algorithm for embedded real-time systems with a special focus on latencies. The algorithm is part of a HardwareSoftware-System that realizes fast reactions on visual stimuli in highly dynamic environments. There is furthermore the constraint to use low-cost hardware to build the system. Our system is implemented on a RoboCup middle size league prototype robot. computer vision, color segmentation, embedded systems, low latency, RoboCup
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Today most low-cost robotic systems navigate very slowly, e.g if you watch a RoboCup game you will see a lot of slowly moving robots. There are two reasons for this: At first, mostly commercially available platforms are used. Because of their widespread usage they are built to be safe in a lot of different areas, thus they are comparatively slow. The second reason is the system architecture. Often PCs are used to control the robot. There are some major drawbacks on PCs because they are not designed to be used as an embedded real-time system. They lack special hardware to control all sensors and actors and the operating system often has no real-time capabilities. There often arise high latencies between an event and the reaction of the system. We are building a robot which is capable of navigating safely through a RoboCup field with a speed of up to 20 km/h. But there is one major constraint: usage of low-cost hardware for building such the robot. 1
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Every robotic system consists of three major parts: The SHUFHSWLRQ, the SURFHVVLQJ and the PDQLSXODWLRQ. For each of these parts we use microcontrollers which are specialized on their tasks. The only sensors we use are consumer electronic analog video cameras because of their low price. We developed a color image segmentation algorithm especially for embedded real-time systems. During the last years a lot of color image segmentation algorithms have been proposed [1], but only little attention has been paid to minimizing latency. Thus we built a system with only vision-based perception and a behaviorbased control system which is directly coupled with the perception and the actors. A good overview of behavior-based robotics is given in [4]. This paper presents a color segmentation algorithm as part of the visionbased perception of our system. The focus is on minimizing the latency of the vision part. The algorithm meets the following requirements which suffice for the RoboCup scenario: ½ It has to be able to analyze 25 frames per second ½ There are no predefined colors for the segmentation process. ½ The shape of the objects is not relevant. The algorithm should only yield the position and size of the objects. ½ It has to cope with the YUV color-space because most image hardware provide the data using this color space. Detailed information about this color space is given on [5].
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Somehow similar to our work is the Polly System built in 1993 at the MIT [6]. One design goal was to use off-the-shelf low-cost hardware. So the only sensor input was one analog camera. They realized a task-based vision system capable of analyzing a 64x48 grey-scale image at 15 hertz. The control system had different layers and the low-level navigation also used behavior-based programming techniques. Newer robots have been built at the MIT based on the Polly System using the Cheap Vision Hardware [7]. Our system uses 352x288 pixel color images as input which permits higher flexibility and also analyzes the images with 25 Hz. At CMU in Pittsburgh a fast color segmentation algorithm and implementation for robots called CMVision has been developed in 2000 [8]. It can discriminate 32 different colors organized in color cubes which has to be defined statically. So the algorithm is very sensible to changing lightning
conditions. Compared to CMVision and other fast color segmentation algorithms our color segmentation algorithm does not use any predefined colors. An algorithm for fast and robust segmentation of natural color scenes has been proposed in [9]. The algorithm called CSC (Color Structure Code) is based on hierarchical region-growing on a special hexagonal topology. The system is applied in two reactive applications from the field of autonomous vehicle guidance. Another very low-cost active vision system for embedded microcontrollers has been proposed in 1997 [10]. It uses a special frame grabber chip in conjuction with a 8-bit microcontroller.
