Automatic Crack Detection in Built Infrastructure Using Unmanned Aerial Vehicles

This paper addresses the problem of crack detection which is essential for health monitoring of built infrastructure. Our approach includes two stages, data collection using unmanned aerial vehicles (UAVs) and crack detection using histogram analysis. For the data collection, a 3D model of the structure is first created by using laser scanners. Based on the model, geometric properties are extracted to generate way points necessary for navigating the UAV to take images of the structure. Then, our next step is to stick together those obtained images from the overlapped field of view. The resulting image is then clustered by histogram analysis and peak detection. Potential cracks are finally identified by using locally adaptive thresholds. The whole process is automatically carried out so that the inspection time is significantly improved while safety hazards can be minimised. A prototypical system has been developed for evaluation and experimental results are included.Comment: In proceeding of The 34th International Symposium on Automation and Robotics in Construction (ISARC), pp. 823-829, Taipei, Taiwan, 201

Joint Rectification and Stitching of Images Formulated as Camera Pose Estimation Problems

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2015. 8. 조남익.This dissertation presents a study of image rectification and stitching problems formulated as camera pose estimation problems. There have been many approaches to the rectification and/or stitching of images for their importance in image processing and computer vision areas. This dissertation adds a new approach to these problems, which finds appropriate optimization problems whose solutions give camera pose parameters for the given problems. Specifically, the contribution of this dissertation is to develop (i) a new optimization problem that can handle image rectification and stitching in a unified framework through the pose estimation formulation, and (ii) a new approach to planar object rectification problem which is also formulated as an optimal homography estimation problem. First, a unified framework for the image rectification and stitching problem is studied, which can handle both assumptions or conditions that (i) the optical center of camera is fixed or (ii) the camera captures a plane target. For this, the camera pose is modeled with six parameters (three for the rotation and three for the translation) and a cost function is developed that reflects the registration errors on a reference plane (image stitching results). The designed cost function is effectively minimized via the Levenberg-Marquardt algorithm. From the estimated camera poses, the relative camera motion is computed: when the optical center is moved (i.e., the camera motion is large), metric rectification is possible and thus provides rectified composites as well as camera poses are obtained. Second, this dissertation presents a rectification method for planar objects using line segments which can be augmented to the previous problem for further rectification or performed independently to single images when there are planar objects in the image such as building facades or name cards. Based on the 2D Manhattan world assumption (i.e., the majority of line segments are aligned with principal axes), a cost function is formulated as an optimal homography estimation problem that makes the line segments horizontally or vertically straight. Since there are outliers in the line segment detection, an iterative optimization scheme for the robust estimation is also developed. The application of the proposed methods is the stitching of many images of the same scene into a high resolution image along with its rectification. Also it can be applied to the rectification of building facades, documents, name cards, etc, which helps the optical character recognition (OCR) rates of texts in the scene and also to improve the recognition of buildings and visual qualities of scenery images. In addition, this dissertation finally presents an application of the proposed method for finding boundaries of document in videos for mobile device based application. This is a challenging problem due to perspective distortion, focus and motion blur, partial occlusion, and so on. For this, a cost function is formulated which comprises a data term (color distributions of the document and background), boundary term (alignment and contrast errors after the contour of the documents is rectified), and temporal term (temporal coherence in consecutive frames).1 Introduction 1 1.1 Background 1 1.2 Contributions 2 1.3 Homography between the i-th image and pi_E 4 1.4 Structure of the dissertation 5 2 A unified framework for automatic image stitching and rectification 7 2.1 Related works 7 2.2 Proposed cost function and its optimization 8 2.2.1 Proposed cost function 12 2.2.2 Optimization 13 2.2.3 Relation to the model in [1] 14 2.3 Post-processing 15 2.3.1 Classification of the conditions 15 2.3.2 Skew removal 16 2.4 Experimental results 18 2.4.1 Quantitative evaluation on metric reconstruction performance 19 2.4.2 Determining the capturing environment 21 2.4.3 Experiments on real images 25 2.4.4 Applications to document image stitching and more results 28 2.5 Summary 28 3 Rectification of planar targets based on line segments 31 3.1 Related works 31 3.1.1 Rectification of planar objects 32 3.1.2 Rectification based on self calibration 33 3.2 Proposed rectification model 33 3.2.1 Optimization-based framework 36 3.2.2 Cost function based on line segment alignments 37 3.2.3 Optimization 38 3.3 Experimental results 40 3.3.1 Evaluation metrics 40 3.3.2 Quantitative evaluation 41 3.3.3 Computation complexity 45 3.3.4 Qualitative comparisons and limitations 45 3.4 Summary 52 4 Application: Document capture system for mobile devices 53 4.1 Related works 53 4.2 The proposed method 54 4.2.1 Notation 54 4.2.2 Optimization-based framework 55 4.3 Experimental results 62 4.3.1 Initialization 65 4.3.2 Quantitative evaluation 65 4.3.3 Qualitative evaluation and limitations 66 4.4 Summary 67 5 Conclusions and future works 75 Bibliography 77 Abstract (Korean) 83Docto

An in Depth Review Paper on Numerous Image Mosaicing Approaches and Techniques

Image mosaicing is one of the most important subjects of research in computer vision at current. Image mocaicing requires the integration of direct techniques and feature based techniques. Direct techniques are found to be very useful for mosaicing large overlapping regions, small translations and rotations while feature based techniques are useful for small overlapping regions. Feature based image mosaicing is a combination of corner detection, corner matching, motion parameters estimation and image stitching.Furthermore, image mosaicing is considered the process of obtaining a wider field-of-view of a scene from a sequence of partial views, which has been an attractive research area because of its wide range of applications, including motion detection, resolution enhancement, monitoring global land usage, and medical imaging. Numerous algorithms for image mosaicing have been proposed over the last two decades.In this paper the authors present a review on different approaches for image mosaicing and the literature over the past few years in the field of image masaicing methodologies. The authors take an overview on the various methods for image mosaicing.This review paper also provides an in depth survey of the existing image mosaicing algorithms by classifying them into several groups. For each group, the fundamental concepts are first clearly explained. Finally this paper also reviews and discusses the strength and weaknesses of all the mosaicing groups

Procedures for condition mapping using 360° images

The identification of deterioration mechanisms and their monitoring over time is an essential phase for conservation. This work aimed at developing a novel approach for deterioration mapping and monitoring based on 360° images, which allows for simple and rapid data collection. The opportunity to capture the whole scene around a 360° camera reduces the number of images needed in a condition mapping project, resulting in a powerful solution to document small and narrow spaces. The paper will describe the implemented workflow for deterioration mapping based on 360° images, which highlights pathologies on surfaces and quantitatively measures their extension. Such a result will be available as standard outputs as well as an innovative virtual environment for immersive visualization. The case of multi-temporal data acquisition will be considered and discussed as well. Multiple 360° images acquired at different epochs from slightly different points are co-registered to obtain pixel-to-pixel correspondence, providing a solution to quantify and track deterioration effects

CleanPage: Fast and Clean Document and Whiteboard Capture

The move from paper to online is not only necessary for remote working, it is also significantly more sustainable. This trend has seen a rising need for the high-quality digitization of content from pages and whiteboards to sharable online material. However, capturing this information is not always easy nor are the results always satisfactory. Available scanning apps vary in their usability and do not always produce clean results, retaining surface imperfections from the page or whiteboard in their output images. CleanPage, a novel smartphone-based document and whiteboard scanning system, is presented. CleanPage requires one button-tap to capture, identify, crop, and clean an image of a page or whiteboard. Unlike equivalent systems, no user intervention is required during processing, and the result is a high-contrast, low-noise image with a clean homogenous background. Results are presented for a selection of scenarios showing the versatility of the design. CleanPage is compared with two market leader scanning apps using two testing approaches: real paper scans and ground-truth comparisons. These comparisons are achieved by a new testing methodology that allows scans to be compared to unscanned counterparts by using synthesized images. Real paper scans are tested using image quality measures. An evaluation of standard image quality assessments is included in this work, and a novel quality measure for scanned images is proposed and validated. The user experience for each scanning app is assessed, showing CleanPage to be fast and easier to use

Toward the vision based supervision of microfactories through images mosaicing.

International audienceThe microfactory paradigm means the miniaturisation of manufacturing systems according to the miniaturisation of products. Some benefits are the saving of material, energy and place. A vision based solution to the problem of supervision of microfactories is proposed. It consists in synthetising a high resolution global view of the work field and real time inlay of local image in this background. The result can be used for micromanipulation monitoring, assistance to the operator, alarms and others useful informations displaying

Synthesizing a virtual imager with a large field of view and a high resolution for micromanipulation.

International audiencePhoton microscope connected with a camera is the usual imager required in micromanipulation applications. That microimager gives high resolution views, but the corresponding field of view are very narrow and do not allow the vision of the entire workfield. The classical solution consists in using multiple views imaging system: a high resolution imager for local view and a low resolution imager for global view. We are developing an alternative solution based on image mosaicing that requires only one microimager. The views from that real microimager are associated in order to achieve a virtual microimager which combines a large field of view with a high resolution