Zhang Jianqing

Genetic feature selection for texture classification

This paper presents a novel approach to feature subset selection using genetic algorithms. This approach has the ability to accommodate multiple criteria such as the accuracy and cost of classification into the process of feature selection and finds the effective feature subset for texture classification. On the basis of the effective feature subset selected, a method is described to extract the objects which are higher than their surroundings, such as trees or forest, in the color aerial images. The methodology presented in this paper is illustrated by its application to the problem of trees extraction from aerial images.

Image Relaxation Matching Based on Feature Points for DSM Generation

In photogrammetry and remote sensing, image matching is a basic and crucial process for automatic DEM generation. In this paper we presented a image relaxation matching method based on feature points. This method can be considered as an extention of regular grid point based matching. It avoids the shortcome of grid point based matching. For example, with this method, we can avoid low or even no texture area where errors frequently appear in cross correlation matching. In the mean while, it makes full use of some mature techniques such as probability relaxation, image pyramid and the like which have already been successfully used in grid point matching process. Application of the technique to DEM generaton in different regions proved that it is more reasonable and reliable.

Change detection based on DSM and image features in urban areas

On the basis of stereo image analysis, the change detection of man-made objects in urban areas is introduced. Information of the height of man-made objects can be applied to reinforce their change detection. By comparison between the new and old DSMs, the changed regions are extracted. However, our aim is to detect changes of man-made objects in urban area and further in the potential areas by the means of line-feature matching and gradient direction histogram. The experiments based on the aerial images from Japan have proven that the algorithm is correct and efficient.

Rapid texture mapping from image sequences for building geometry model

An effective approach, mapping the texture for building model based on the digital photogrammetric theory, is proposed. The easily-acquired image sequences from digital video camera on helicopter are used as texture resource, and the correspondence between the space edge in building geometry model and its line feature in image sequences is determined semiautomatically. The experimental results in production of three-dimensional data for car navigation show us an attractive future both in efficiency and effect.

HOUSE CHANGE DETECTION BASED ON DSM OF AERIAL IMAGE IN URBAN AREA

The change of house often brings on the change of DSM in an area over different periods. If we can apply information of the height of houses to reinforce the house change detection, the reliability and efficiency of detection methods will be improved greatly. From this viewpoint, a new approach taking advantage of both height data from an image pair and image data is proposed to detect the house change in urban area and is called “data fusion technology”.

Change detection from aerial images acquired in different durations

Because of quick development of cities, the update of urban GIS data is very important. Change detection is the base of automatic or semi-automatic data update. One way of change detections in urban area is based on old and new aerial images acquired in different durations. The corresponding theory and experiments are introduced and analyzed in this paper. The main procedure includes four stages. The new and old images have to be registered firstly. Then image matching, based on the maximum correlation coefficient, is performed between registered images after the low contrast areas have been removed. The regions with low matching quality are extracted as candidate changed areas. Thirdly, the Gaussian-Laplacian operator is used to detect edges in candidate changed areas on both the registered images, and the straight lines are detected by Hough transformation. Finally, the changed houses and roads can be detected on the basis of straight line matching in candidate changed areas between registered images. Some experimental results show that the method introduced in this paper is effective.

Flexible planar-scene camera calibration technique

A flexible camera calibration technique using 2D-DLT and bundle adjustment with planar scenes is proposed. The equation of principal line under image coordinate system represented with 2D-DLT parameters is educed using the correspondence between collinearity equations and 2D-DLT. A novel algorithm to obtain the initial value of principal point is put forward. Proof of Critical Motion Sequences for calibration is given in detail. The practical decomposition algorithm of exterior parameters using initial values of principal point, focal length and 2D-DLT parameters is discussed elaborately. Planar-scene camera calibration algorithm with bundle adjustment is addressed. Very good results have been obtained with both computer simulations and real data calibration. The calibration result can be used in some high precision applications, such as reverse engineering and industrial inspection.

On Invariant-based Object's Locating Method

It is presented that one hierarchical method based on invariant feature for object recognition and location in complex background. For rectangle mark, local features are constructed and extracted firstly. Approximate location can be detected by aggregating local features. The precise location can be measured by template matching and extract structure lines. So it is realized that marks are located in complex background automatically.

3D Motion Parameters Determination Based on Binocular Sequence Images

Exactly capturing three dimensional (3D) motion information of an object is an essential and important task in computer vision, and is also one of the most difficult problems. In this paper, a binocular vision system and a method for determining 3D motion parameters of an object from binocular sequence images are introduced. The main steps include camera calibration, the matching of motion and stereo images, 3D feature point correspondences and resolving the motion parameters. Finally, the experimental results of acquiring the motion parameters of the objects with uniform velocity and acceleration in the straight line based on the real binocular sequence images by the mentioned method are presented.

New mathematical model based on affine transformation for remote sensing image with high resolution

This paper calculates the parameters of image position and orientation, proposes a mathematical model and adopts a new method with three steps of transformations based on parallel ray projection. Every step of the model is strict, and the map function of each transformation is the first order polynomials and other simple function. The final calculation of the parameters is for the linear equations with good status. As a result, the problem of the relativity of image parameter calculation is solved completely. Some experiments are carried out.