Detection and recognition of objects in images has been applied in many areas. The key point in object detection or recognition is the image segmentation. How to robustly extract the interesting objects from complex background will greatly determine the final detection or recognition result. Aiming at developing a vision system for the robot based on natural object detection or recognition, the approach of robust segmentation, the scheme of object detection and recognition, and some real examples of object detection and recognition in mobile robot navigation are researched. The main contributions of the works reported in this thesis are as follows: 1. A robust approach for natural image segmentation is proposed. Most of the existing methods for natural image segmentation simultaneously considering the texture and contour features are based on the recursive process that is much time-consuming. Therefore, they are not suitable to the cases requiring real-time processing. In order to apply the segmentation methods for natural images in the real-time applications, an approach derived from Mean Shift is developed. The experimental results show that the different images under various illuminations and backgrounds can be stably partitioned into some meaningful regions. In addition, the parameters used in segmentation are adjusted by the real vision task. 2. Based on the proposed robust approach for natural image segmentation, a new scheme of object detection and recognition is presented. The new scheme includes following important steps: roughly segmenting the images with big parameters in the proposed natural image segmentation, extracting the interesting regions with meticulous image processing, and verifying or recognizing the object candidates with object models. 3. A detection approach for the door and the floor used in robot navigation is designed. The detection procedure is based on the robust natural image segmentation and the robust statistical modeling of objects. 4. A character recognition system under natural scenes used in robot navigation is designed. Compared with other character recognition systems for robot navigation, this system is much robust and resistant to the noise. The proposed approach for natural image segmentation has not only a robust result, but also a fast computing speed which makes it can be used in robot navigation. The detection or recognition methods of the door, the floor and the characters in natural scene can also be used in the other object detection or recognition.
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