Extracting road centrelines from high-resolution satellite images using active window line segment matching and improved SSDA

Based on analyzing the traditional image matching algorithms, a fast image matching method, which integrates improved sequential similarity detection algorithm (SSDA) and wavelet transformation, is presented in this paper. Firstly, some basic principles of SSDA image matching and wavelet transformation are introduced. Secondly, according to the shortcoming of traditional SSDA algorithm, a new SSDA algorithm is studied for improving the determining velocity of the threshold in SSDA searching match. By integrating wavelet transformation, an integrated matching algorithm is given out. Finally, the new method is compared with the traditional matching algorithms in experiments. The experimental results show that the new method has higher efficiency and accuracy in image matching and is suitable for the realization of real-time underwater navigation.

Extracting road information from high-resolution satellite images is complex and hardly achieves by exploiting only one or two modules. This paper presents a multi-stage method, consisting of automatic information extraction and semi-automatic post-processing. The Multi-scale Enhancement algorithm enlarges the contrast of human-made structures with the background. The Statistical Region Merging segments images into regions, whose skeletons are extracted and pruned according to geometry shape information. Setting the start and the end skeleton points, the shortest skeleton path is constructed as a road centre line. The Bidirectional Adaptive Smoothing technique smoothens the road centre line and adjusts it to right position. With the smoothed line and its average width, a Buffer algorithm reconstructs the road region easily. Seen from the last results, the proposed method eliminates redundant non-road regions, repairs incomplete occlusions, jumps over complete occlusions, and reserves accurate road centre lines and neat road regions. During the whole process, only a few interactions are needed.

Template matching is a basic algorithm for image processing, and real-time is a crucial requirement of object tracking. For real-time tracking, a fast template matching algorithm based on grey prediction is presented, where computation cost can be reduced dramatically by minimizing search range. First, location of the tracked object in the current image is estimated by Grey Model (GM). GM(1,1), which is the basic model of grey prediction, can use some known information to foretell the location. Second, the precise position of the object in the frame is computed by template matching. Herein, Sequential Similarity Detection Algorithm (SSDA) with a self-adaptive threshold is employed to obtain the matching position in the neighborhood of the predicted location. The role of threshold in SSDA is important, as a proper threshold can make template matching fast and accurate. Moreover, a practical weighted strategy is utilized to handle scale and rotation changes of the object, as well as illumination changes. The experimental results show the superior performance of the proposed algorithm over the conventional full-search method, especially in terms of executive time.

An approach of fast image mosaic is presented, which involves image matching and image intensity smoothing. Image matching includes two procedures, i.e. rough matching and fine matching. In rough matching, the overlapped regions of two adjacent images to be mosaicked are segmented to binary image at first. Then the binary images are filtered by open operation of mathematic morphologic method. In the binary image region of the reference image, feature template is searched and extracted on a given rule. Via XOR operation of the feature template and search region, some possible matching positions in the overlapped region of the other image are got. In the fine matching, the sequential similarity detection algorithm (SSDA) is adopted to perform matching computation in the small regions near the positions got in the rough matching, and then the relative position offsets in X-orientation and Y-orientation between the two adjacent images are got. Based on the result of the image matching, the two images are stitched. An approach of seam-line smoothing is adopted to adjust the intensity of the overlapped area. Simulation experimental results show that the approach greatly improves the operation speed, while the precision remains fine, so it can be applied in real-time mosaicking.

Automatic recognition of welding defects in real-time radiography

In allusion to the colored image matching characteristic in the system of robot view navigation, SSDA (the sequential similarity detection algorithm) is improved and adaptive genetic algorithm is brought in; meanwhile, level-divided search strategy connective with rough and exact matching. The improved algorithm can enhance the image matching speed with no matching accuracy reduced, so that real-time requirements of robot view navigation can be met and robot view navigation will be of preferable robustness.

A supercomputer-based software which enables reconstruction of a three-dimensional shape without human assistance using a stereo-pair of scanning electron micrographs has been developed. It is based upon computer image processing and pattern recognition techniques, and can reconstruct a three-dimensional shape of a wide variety of fracture surfaces of corrosion fatigue as well as crack initiation sites in an aggressive environment line a corrosion pit. We discuss the optimum algorithm according to the morphology of the fracture surfaces. A sequential similarity detection algorithm is available in transgranular fatigued surfaces, whereas in the case of corrosion fatigue fracture surfaces and crack initiation sites, the mutual correlation coefficient technique is well suited. The shape and size of the window area, and the run time required in reconstruction are also discussed.

This paper visualizes the cutting mechanism of A1100–H18 and A1100–O of commercially pure aluminum for the measurement of the strain rate distribution near a cutting edge in orthogonal cutting. The distribution is measured using various methods in order. The methods are in-situ observation of cutting process in SEM, inputting image data, a computer image processing, calculating displacements by SSDA (Sequential Similarity Detection Algorithm) and calculating strain rates by FEM. The main results obtained are as follows: (1) It enables to measure a microscopic displacement near a cutting edge. (2) Cutting mechanism was made clear by measuring a strain rate distribution. (3) In cutting A1100–O, small fluctuations of the strain rate distribution were observed.

An approach of image mosaic based on binary image region matching is presented and applied in remote sensing serial image processing. Adopted the Nearest-neighbour interpolation, the original images are rectified on the basis of the values of external orientation elements of the camera installed on the unmanned aerial vehicle (UAV). Image matching includes two procedures, i.e. rough matching and fine matching. In rough matching, the area coverage of overlapped regions between two consecutive images to be stitched is determined approximately at first. Both of the overlapped regions of the two images are processed to binary image, and then the binary images are filtered by mathematic morphologic method. In the appointed binary image region of the former image, feature template is searched and extracted. Through the XOR operation of the feature template and search region, some possible matching positions in the overlapped region of the latter image are obtained. In the fine matching, the sequential similarity detection algorithm (SSDA) is adopted to perform matching computation in the some small regions near the positions extracted in the rough matching, and then the relative position offsets in X-orientation and Y-orientation between the two consecutive images are obtained. Based on the result of the image matching, the two images are stitched. Experimental results by simulation show that the approach presented in the paper greatly improves the operation speed, while the precision remains fine, than it can be applied in real-time mosaicking of serial images.

Based on analyzing current independent navigation methods, this paper presents a new underwater navigation system, which is integrated inertial navigation system (INS) and side scan sonar (SSS). Firstly we introduce the component of the underwater navigation system and the functions of each unit in the system. Then, we study the algorithm of the matching navigation used in the system. A fast image match method by integrating wavelet transform and improved sequential similarity detection algorithm (SSDA) is given out. Based on above researches, we implement simulation experiments. Experimental results show that the system presented in this paper can acquire high navigation accuracy under the background with characteristic seabed relief. Finally, some valuable conclusions and suggestions are given.

In this paper, we propose a novel approach for road width measurement from high resolution satellite or aerial images. The proposed approach has three main steps. First, we extract line segments and road center lines on the given remote sensing images. Second, we could obtain many pairs of parallel lines with width information by computing the positional relationship between each other. Then K-means is performed to cluster these parallel lines into several clusters by the width information of them. Finally, an energy function is introduced to assign the width range of a cluster to each pixel on road center lines, the width range is viewed as the width of the corresponding road segment. Attribute to parallel lines extraction, parallel lines clustering and our energy function, the proposed road width measurement method is able to provide high quality results on road width measurement.

Aiming at the sensitivity of the road centerline extraction algorithm using directional texture to the disturbance in the images, a modified method for road centerlines on high-resolution remote sensing images is proposed based on the directional texture and Kalman Filter. After the initial center points of the road are obtained by directional texture matching, Kalman Filter combined with priori information and observation information of the road center points is applied to track the accurate road center points iteratively. Multiple experiments are designed to verify the reliability and robustness of the algorithm, showing that it can reduce the covering impact of vehicles, trees and shadow on road extraction in high-resolution images with relatively strong robustness and flexibility. The average position deviation is 1.9 pixels, and the average position deviation error is 1.7 pixels.

Spatio-temporal analysis of Kilim River using Very High-Resolution (VHR) satellite image between the years of 2005 and 2012 are vital to assess river morphological changes and erosion detection over the specific time duration. Therefore, this study utilizes remote sensing and Geographical Information System (GIS) capabilities to identify the channel migration and shifting as well as to calculate the rate of erosion and accretion. Classification of the river from Quickbird and WorldView-2 images is carry out using Maximum Likelihood Classification (MLC) technique whereas feature selection tool performs to extract river feature from the raw image. Subsequently, river feature been overlaid to identify the changes of riverbank pattern and to calculate the rate of riverbank erosion in terms of area. The result shows the total area of erosion is 27252.959 m2 and the total area of accretion is 6079.999 m2. A maximum erosion of 6993.102 m2 detected at Section E while maximum accretion of 681.026 m2 spotted at Section D. The rates of riverbank erosion are 3406.62 m2/year while the rates for accretion are 759.999 m2/years between 2005 and 2012. Hence, the output of this study enables Langkawi Development Authority (LADA) and other stakeholders to recognize the specific location, which severely affected by erosion and accretion as well as to spot the area experienced huge river channel shifting.

A gully erosion assessment model for the Chinese Loess Plateau based on changes in gully length and area

If the usability of orthophotos of aerial images and high-resolution satellite images in cadastre renewal works is ensured, the state cadastre can be maintained and constantly updated. For this purpose, three pilot fields in Konya, Adana and Şanlıurfa were selected. In these fields, land surveys were made with a CORS method by using GPS. The coordinates were obtained by using orthophotos in Konya (1/2000 scale) and in Adana (1/5000 scale) and orthophotos with 1/5000 scale obtained from WorldView-2 high-resolution satellite images in Şanlıurfa. One aim was to establish the positional accuracy of the data obtained from digital orthophotos and area accuracy in comparison with cadastral areas by presuming that the land surveys were accurate. In light of the discovered results, comments on the usability of orthophotos obtained from aerial images and high-resolution satellite images in renewal cadastre were made.