This paper proposed a new stable algorithm based on feature point matching, which can be used in image registration under shift and rotation. The new method firstly extracts feature points in the first image of an image sequence and then searches the matching points in the consecutive images. Different from conventional methods, it adopts constrain of distance to revise matching and removing false matching, and also adopts projection of pixel to filter feature points and choose many possible matching points for one reference feature point, which makes it fast and reliable. Experiments prove this method is practical and reliable.
Te paper proposed a new segmentation method, which is based on the relation stable-state. The relation stable-state is derived from the fact that the contour of an object may be enlarged or shrunk while the threshold is changing, but times that boundary points visited by contours is more than times that inner points visited by contours. This relation is usual stable. Minimum area and edge intensity are the only two parameters needed in it. Under the control of these two parameters, it chooses contours in the original image; sums them into a contour image; extracts contours in the contour image, does merge-split process and region growing step by step. In fact, it integrated gray value, edge information and space connectivity smartly. Experiments show it can be applied to extract objects with multi-level perfectly even if the image is non-uniform illumination, thus it is more general and practical.
Road cracks in the highway surface are very dangerous to traffic. They should be found and repaired as early as possible. So we designed the system of auto detecting cracks in the highway surface. In this system, there are several key steps. For instance, the first step, image recording should use high quality photography device because of the high speed. In addition, the original data is very large, so it needs huge storage media and some effective compress processing. As the illumination is affected by environment greatly, it is essential to do some preprocessing first, such as image reconstruction and enhancement. Because the cracks are too tiny to detect, segmentation is rather difficult. This paper here proposed a new segmentation method to detect such tiny cracks, even 2mm-width ones. In this algorithm, we first do edge detecting to get seeds for line growing in the following. Then delete the false ones and get the information of cracks. It is accurate and fast enough.
Finding line segments in an intensity image is one of the most fundamental issues in computer vision and other industry applications. Many methods have been presented, but robust line segment extraction is still a difficult and open problem. In this paper a local window method based on line-model to extract lineal features from low quality image is described. The method utilizes blob-coloring technique to extract potential line-blob in a local window area, then a line segment is discriminate using the line-model.
In the paper, Laser Measurement System (LMS) is used to monitor region in ship lock of the Three Gorges Project. Several methods are carried out to detect objects in the region. First, in order to determine whether there are ships in detected region, a distance difference integral method is given. Second, in order to decrease the random noise affection, the neutralization and the relativity of the fore-and-aft data are used to eliminate the noise and to eliminate misjudge from the random data. Third, two LMSs are installed to trace the motive object, a fixed LMS detects a linear region, and the other LMS can be rotated to scan a plane region in ship lock. As the fix LMS detected some motive objects, the other LMS begins to rotate and trace changed region and to determine whether there are objects in detected region. Finally, Laser Measurement System is tested in SanBo ship lock in ZheJiang province of China. All the methods are very effective. And the system will be installed in permanent ship lock of the Three Gorges Project in 2003. The system will keep the safety of the lock.
In the paper, an on-line detecting system for ships in lock is presented. The system has three functions: (1) judging whether there are ships in lock in time; (2) detecting whether ships cross the forbidden lines in lock; (3) observing whether there are ships out of lock. First, a Gaussian probability distribution model (probability field) is generated from the gray-level histogram to diminish the affection of shades of buildings and white speckles by bright light. Second a fundamental optical flow method based on spatio-temporal intensity derivatives is used to calculate normal velocity field of image sequences. Third, a probability velocity field is defined and generated by combining the velocity field with probability field. Two calculating methods about probability velocity field are presented, one method is multiplying probability value with magnitude of velocity field, and the other is using probability field to compute the velocity field. Finally, a movement block detection method is designed according to probability velocity field. And the method not only detects the size and position of movement blocks, but also obtains the direction of movement blocks. These methods have been tested and installed successfully in the temporary ship lock of the Three Gorges Project (TGP).
The paper presents one effective method for ship recognition in the ship lock. The outdoors environment is very complexity in which there are shade, waves and speckles caused by the sunlight and wind or motion of ships. The accuracy of recognition is depended on the accuracy of disturb area detection. It analyzes their characters on gray level and structure, proposes a new method to form a special histogram of only those pixels besides the boundary. This histogram is fit for small object segment and also large. At the end, the features for recognition based on statistic are presented. The long time running in the temporary ship lock of Three Gorges Project proves the error rate of judging is less than three thousandth just using the statistic features and less than one over ten thousands cooperating with the others.
In the paper, an on-line detection system for ships in lock of is presented. The system has three functions: (1) Judging whether there are ships in lock in time; (2) Detecting whether ships cross the forbidden lines in lock; (3) Observing whether there are ships out oflock. Therefore, the system not only maintains the normal and fast working of lock,but also ensures safety of lock. The detection method is based on the optical flow of gray-level probability.
Road segmentation is one of the most preliminary and important tasks for the road following and planning of the Autonomous Land Vehicle (ALV), since the efficiency of road segmentation has direct effect on the reliability of road following and planning, and consequently the speed of ALV. Therefore, road segmentation has been extensively studied, and a variety of methods for color road segmentation have been proposed, since color images contain more information of road than gray level images do. In most of the existing color road segmentation approaches, a best discriminant vector, which is a linear transformation of color vector (r,g,b), was used to project and classify a point in color space, and only one such projection was used in the segmentation, which may lead to instability of segmentation under variant circumstances. This presentation proposed a new color road segmentation method in which a pyramid based data structure and the corresponding region splitting and combination techniques for the classification of sensed areas are adopted. At the same time, two transformations of the (R,G,B) color space, and data fusion technique are used to increase the efficiency of the road segmentation. Experiment results are presented to illustrate the performance of this approach.