Area-based Matching Algorithm Research Articles

Evaluation of an Area-Based matching algorithm with advanced shape models

Abstract. Nowadays, the scientific institutions involved in planetary mapping are working on new strategies to produce accurate high resolution DTMs from space images at planetary scale, usually dealing with extremely large data volumes. From a methodological point of view, despite the introduction of a series of new algorithms for image matching (e.g. the Semi Global Matching) that yield superior results (especially because they produce usually smooth and continuous surfaces) with lower processing times, the preference in this field still goes to well established area-based matching techniques. Many efforts are consequently directed to improve each phase of the photogrammetric process, from image pre-processing to DTM interpolation. In this context, the Dense Matcher software (DM) developed at the University of Parma has been recently optimized to cope with very high resolution images provided by the most recent missions (LROC NAC and HiRISE) focusing the efforts mainly to the improvement of the correlation phase and the process automation. Important changes have been made to the correlation algorithm, still maintaining its high performance in terms of precision and accuracy, by implementing an advanced version of the Least Squares Matching (LSM) algorithm. In particular, an iterative algorithm has been developed to adapt the geometric transformation in image resampling using different shape functions as originally proposed by other authors in different applications.

Improved Seamless Cloning based Image In painting

Image in-painting is a restoration of image parts which are missing either accidentally or intentionally, and also image recovery is a research hot spot in the computer graphics and computer vision in the current. Two major inpainting techniques are introduced, those are PDE-based and Texture based algorithms. In PDE-based technique a conventional image matching techniques may be classified as either area based or feature based methods. In this paper, taking an input image and apply Pre-processing, After we get gray image and contour extraction algorithm is used to extract the contour features of damaged area, which determine the contour feature location. After that Matching algorithms play a key role in deciding correspondences between two image scenes. Area-based matching algorithm is used to search alternative matching area .Contour-based Similarity Distance function (CSD) is used to determine the most similar matching area. According to the damaged area and the matching area, the source cloning domains and target cloning domains of Seamless Cloning algorithm is improved. Using mean value coordinates to achieve regional pixel cloning from the source cloning domain to the target cloning domain. Finally, the improved SC algorithm is used to repair the image. Experimental results confirm the effectiveness of the proposed algorithm, and that the method can not only repair small-scale scratches, but also repair a large area damaged areas.

FEATURE ANALYSIS FOR MULTI-WINDOW MATCHING

Abstract. Image matching is a practical way to build up the relationship between point pairs. In remote sensing and photogrammetry applications, area-based matching algorithms are usually used under control environment, such as fixing exterior orientation parameters, to reach high matching precision. In order to improve the reliability of image matching, area-based matching algorithms are frequently performed with image pyramid and epipolar constraints. Thus, Central-Left-Right matching (CLR matching) is proposed to enhance the reliability. The method is designed to cope with unreliable matching when the objects are with surface discontinuity. The CLR matching puts a candidate point in the center, left and right windows. Thus, the elements of target window and search window may be corresponded to the same objects if the candidate point is located in a vertical edge. In addition, the directions of features in the image may be varied because of the object diversity. Thus, the CLR matching would be better to combine with multi-window operation in accordance with the feature direction. This paper analyzed the feature direction first followed by the multi-window matching. The major works in this investigation contain feature extraction, feature analysis, and image matching. The experiments compared the results of traditional image matching, CLR matching, and multi-window matching. The experimental results indicate that the proposed method improves the accuracy of image matching.

Three-dimensional reconstruction of cleavage fracture surface for duplex stainless steel

A reconstruction system of three-dimensional topography by parallax measurement of stereoscopic scanning electron microscopy has been developed. A digital elevation of the fracture surface was calculated from the relative displacement between corresponding positions using an area-based matching algorithm, and then digital elevation models of the three-dimensional topography were reconstructed on the monitor of a personal computer. The system was applied to the ductile fracture surfaces of duplex stainless steel. The reconstructed images obviously revealed an elongated dimple fracture originating from inclusions and cleavage cracks arrested by austenite grain. The reconstruction of the cleavage fracture surface of type 444 ferritic stainless steel was also made, and the elevation of cleavage steps of the river pattern was detected.