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24th ISPRS Congress on Imaging Today, Foreseeing Tomorrow

作者： Benz, Christian Rodehorst, Volker Bauhaus Univ Weimar Comp Vis Engn Weimar Germany

In order to appropriately measure properties in 3D models, accurate georeferencing plays a vital role in structural health monitoring. For that purpose, control points are attached to the surface of the structure and measured geodetically. These points can be recovered in the virtual model and associated with the geodetic measurements. Automating the process of detecting and associating control points and geodetic measurements, facilitates the accurate georeferencing of large 3D models. While the number of marker types for control points is steadily increasing, this work claims that - under a plausible assumption - comparatively simple and commonly used marker designs can serve for accurate and robust georeferencing. By assuming that control points are asymmetrically distributed over the surface of the structure, the correspondence of points is determined by their geometric interrelation. In this work, an image-based detector for relatively simple control point types is proposed, applying transfer learning on hierarchical multi-scale attention (HMA) (Tao et al., 2020). For associating detected and geodetically measured points, a RANSAC-based procedure is presented that determines a geometrically consistent transformation between detected and measured points.

关键词： control point detection Semantic Segmentation Deep Learning Georeferencing point Cloud Registration

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Robust vision-based method for wing deflection angle measurement with defocus images

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MEASUREMENT 2022年 189卷

作者： Wang, Yanzhe Yang, Feng Shan, Dandan Fang, Qiang Wei, Yanding Zhejiang Univ Coll Mech Engn State Key Lab Fluid Power & Mechatron Syst Hangzhou 310027 Peoples R China Zhejiang Univ Coll Mech Engn Key Lab Adv Mfg Technol Zhejiang Prov Hangzhou 310027 Peoples R China AVIC Xian Aircraft Ind Grp Co Ltd Xian 710089 Shaanxi Peoples R China AVIC Shenyang Aircraft Co Ltd Shenyang 110850 Liaoning Peoples R China

The accuracy of existing vision-based angle measurement methods is extremely reduced when the images appear defocus. To solve this problem, a robust center location method for defocus circular targets is proposed and subpixel accuracy of control points can be obtained even with defocus images. Based on this location method, two vision-based angle measurement methods are proposed to measure deflection angles for fixed-axis and movingaxis wings, respectively. These methods are simple and easy to install with no need of prior information of wings' structure or rotation axes. Simulation and real experiments show that the proposed methods have good robustness to image noise and can significantly reduce the measurement errors of defocus images. The proposed methods almost keep unchanging to the results at good focus status, and the measurement accuracy under severe defocus blur state is about 60% higher than that of the state-of-art method for comparison.

关键词： Monocular vision Vision measurement control point detection Defocused image Rotation angle measurement

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Concentric circle grids for camera calibration with considering lens distortion

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OPTICS AND LASERS IN ENGINEERING 2021年 140卷 106527-106527页

作者： Bu, Lingbin Huo, Hongtao Liu, Xiaoyuan Bu, Fanliang Peoples Publ Secur Univ China Sch Informat Network Secur Beijing 100038 Peoples R China

The accuracy of camera calibration depends significantly on the control point detection which customarily subjects to image noise, distortion and resolution. This paper uses concentric circle grids as the calibration pattern and accordingly proposes a robust and accurate control point detection method for camera calibration. Each set of concentric circles on the grids pattern consists of multiple circles whose radii decrease progressively. The geometric structure of multi-hierarchies can not only robustly extract control points from complicated scenarios but also build a voting scheme to avoid numerical instability resulting from the estimation of projected centers. According to the common self-polar triangle of concentric circles and the local sub-pixel edge detection algorithm, we efficiently estimated sub-pixel coordinates of control points under projective transformation. Simulations and real experiments were conducted to demonstrate that the performance of calibration using concentric circle grids is superior to the popular grid patterns with respect to the image noise, distortion and resolution.

关键词： Camera calibration Concentric circle grids control point detection

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A Robust detection Method of control points for Calibration and Measurement With Defocused Images

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2017年第10期66卷 2725-2735页

作者： Ding, Wendong Liu, Xilong Xu, De Zhang, Dapeng Zhang, Zhengtao Chinese Acad Sci Inst Automat Res Ctr Precis Sensing & Control Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 101408 Peoples R China

This paper presents a detection method of control points for the camera calibration and measurement applications, which is robust to defocus. Our method is based on a ground truth, which we call ridge invariance. That is, the positions of broad-brush lines' ridge lines are invariant to defocus blur. First, the ridge invariance is deduced in theory. Then, the methods for ridge point's detection including defocus degree estimation and salience enhancement are deduced. In calibration and measurement experiments, new marks are designed and control points are determined at intersects of the ridge curves. Experiments show that our method can obtain precise calibration and measurement results with images in a large defocus amount range. In the effective defocus amount range, the accuracy of the proposed method almost keeps unchanged to the best values. The proposed method has approximated the same performance as conventional methods at good focus values.

关键词： Camera calibration control point detection defocused image point spread function vision measurement

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PRELAUNCH PHOTOGRAMMETRIC CALIBRATION OF RUSSIAN SATELLITE ELEKTRO-L IMAGERY INSTRUMENTS 23

PRELAUNCH PHOTOGRAMMETRIC CALIBRATION OF RUSSIAN SATELLITE E...

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23rd Congress of the International-Society-for-Photogrammetry-and-Remote-Sensing (ISPRS)

作者： Gektin, U. M. Egoshkin, N. A. Eremeev, V. V. Kuznetcov, A. E. Kochergin, A. M. JSC Russian Space Syst 53 Aviamotornaya Str Moscow 111250 Russia Ryazan State Radio Engn Univ 59-1 Gagarin Str Ryazan 390005 Russia

Technology of prelaunch geometric calibration of multispectral imagery instruments of Russian geostationary satellites "Elektro-L" No.1 and No.2 is considered. Circular control points are used as a test field. Its geometrical model is developed to take distortions in the collimator optical system into account. Multiple observations of a test field at different angles is used to cover the full visual field of a geostationary sensor. New algorithm of circular control point detection is developed and adapted to complex geometry of geostationary imagery. It is capable of processing images formed as a set of separate scans. Under calibration, sensor design parameters and also the law of scanning mirror motion are specified. The paper contains results of the technology approval under prelaunch calibration of MSU-GS sensors for geostationary operational meteorological satellites (GOMS) "Elektro-L" No. 1 and No.2.

关键词： Photogrammetric Geostationary Satellites Sensor Calibration control point detection Geometric Model Acquisition

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Automated control point detection, Registration, and Fusion of Fuzzy Retinal Vasculature Images

Automated Control Point Detection, Registration, and Fusion ...

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IEEE International Conference on Fuzzy Systems

作者： Cao, Hua Brener, Nathan Thompson, Hilary Iyengar, S. S. Ye, Zhengmao Louisiana State Univ Dept Comp Sci Baton Rouge LA 70802 USA LSU Eye Ctr Dept Ophthalmol New Orleans LA 70112 USA Southern Univ Dept Elect Engn Baton Rouge LA 70813 USA

ISBN: (纸本)9781424418183

Multi-modality biomedical images' feature detection, registration, and fusion are usually scene dependent which requires intensive computational effort. A novel automated approach of the multi-modality retinal image control point detection, registration, and fusion is proposed in this paper. The new algorithm is reliable and time efficient, which implements automatic adaptation from frame to frame with a few tunable thresholds. The reference and input images are from two different modalities, i.e., the angiogram grayscale and fundus true color images. Retinal image's properties determine the fuzzy vessel boundaries and bifurcations. The retinal vasculature is extracted using Canny Edge Detector and the control points are detected at the fuzzy vasculature bifurcations using the Adaptive Exploratory Algorithm. Shape similarity criteria are employed to match the control point pairs. The proposed heuristic optimization algorithm adjusts the control points at the sub-pixel level in order to maximize the objective function Mutual-Pixel-Count (MPC). The iteration stops either when f(MPC) reaches the maximal, or when the maximum allowable loop count is reached. The comparative analysis with other existing approaches has shown the advantages of the new algorithm in terms of novelty, efficiency, and accuracy.

关键词： control point detection Biomedical Imaging Biomedical Image Registration Biomedical Image Fusion Fuzzy Vasculature Boundaries Adaptive Exploratory Algorithm Mutual-Pixel-Count Heuristic Optimization

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Angiogram, Fundus, and Oxygen Saturation Optic Nerve Head Image Fusion

Angiogram, Fundus, and Oxygen Saturation Optic Nerve Head Im...

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Conference on Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues VII

作者： Cao, Hua Khoobehi, Bahram Robot Res Lab 298 Coates Hall Baton Rouge LA 70803 USA Louisiana State Univ Hlth Sci Ctr Opt Phys Lab New Orleans LA 70112 USA

ISBN: (纸本)9780819474285

A novel multi-modality optic nerve head image fusion approach has been successfully designed. The new approach has been applied on three ophthalmologic modalities: angiogram, fundus, and oxygen saturation retinal optic nerve head images. It has achieved an excellent result by giving the visualization of fundus or oxygen saturation images with a complete angiogram overlay. During this study, two contributions have been made in terms of novelty, efficiency, and accuracy. The first contribution is the automated control point detection algorithm for multi-sensor images. The new method employs retina vasculature and bifurcation features by identifying the initial good-guess of control points using the Adaptive Exploratory Algorithm. The second contribution is the heuristic optimization fusion algorithm. In order to maximize the objective function (Mutual-Pixel-Count), the iteration algorithm adjusts the initial guess of the control points at the sub-pixel level. A refinement of the parameter set is obtained at the end of each loop, and finally an optimal fused image is generated at the end of the iteration. It is the first time that Mutual-Pixel-Count concept has been introduced into biomedical image fusion area. By locking the images in one place, the fused image allows ophthalmologists to match the same eye over time and get a sense of disease progress and pinpoint surgical tools. The new algorithm can be easily expanded to human or animals' 3D eye, brain, or body image registration and fusion.

关键词： Image Fusion Optic Nerve Head Imaging control point detection Mutual-Pixel-Count

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Automated registration and fusion of the multi-modality retinal images

Automated registration and fusion of the multi-modality reti...

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40th Southeastern Symposium on System Theory

作者： Cao, Hua Brener, Nathan Thompson, Hilary Iyengar, S. S. Ye, Zhengmao Louisiana State Univ Dept Comp Sci Baton Rouge LA 70803 USA Southern Univ Dept Elect Engn Baton Rouge LA 70813 USA

ISBN: (纸本)9781424418060

Biomedical image fusion is generally scene dependent, which requires intensive computational effort. A novel approach of feature-based registration and area-based heuristic optimization fusion of multi-modality retinal images is proposed in this paper. The new algorithm, which is reliable, robust, and time-efficient, has an automatic adaptation from frame to frame with few tunable threshold parameters. The registration approach is based on the retinal vasculature extraction using Canny Edge Detector, and control point identification at the vessel bifurcations using the adaptive exploratory algorithm. The shape similarity criteria are employed to fit the control points. The new fusion approach implements the Mutual-Pixel-Count (MPC) maximization based heuristic optimization procedure, which adjusts the control points at the sub-pixel level. MPC is the new measurement criteria for fusion accuracy being proposed. This study achieved a global maxima equivalent result by calculating MPC local maxima with an efficient computation cost. The new method is a promising step towards useful clinical tools for retinopathy diagnosis, and thus forms a good foundation for further development.

关键词： biomedical image registration and fusion adaptive exploratory algorithm control point detection mutual-pixel-count retinal vasculature extraction heuristic optimization

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A novel automated approach of multi-modality retinal image registration and fusion

A novel automated approach of multi-modality retinal image r...

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作者： Cao, Hua Louisiana State University

学位级别：博士

Biomedical image registration and fusion are usually scene dependent, and require intensive computational effort. A novel automated approach of feature-based control point detection and area-based registration and fusion of retinal images has been successfully designed and developed. The new algorithm, which is reliable and time-efficient, has an automatic adaptation from frame to frame with few tunable threshold parameters. The reference and the to-be-registered images are from two different modalities, i. e. angiogram grayscale images and fundus color images. The relative study of retinal images enhances the information on the fundus image by superimposing information contained in the angiogram image. Through the thesis research, two new contributions have been made to the biomedical image registration and fusion area. The first contribution is the automatic control point detection at the global direction change pixels using adaptive exploratory algorithm. Shape similarity criteria are employed to match the control points. The second contribution is the heuristic optimization algorithm that maximizes Mutual-Pixel-Count (MPC) objective function. The initially selected control points are adjusted during the optimization at the sub-pixel level. A global maxima equivalent result is achieved by calculating MPC local maxima with an efficient computation cost. The iteration stops either when MPC reaches the maximum value, or when the maximum allowable loop count is reached. To our knowledge, it is the first time that the MPC concept has been introduced into biomedical image fusion area as the measurement criteria for fusion accuracy. The fusion image is generated based on the current control point coordinates when the iteration stops. The comparative study of the presented automatic registration and fusion scheme against Centerline control point detection Algorithm, Genetic Algorithm, RMSE objective function, and other existing data fusion approaches has shown the advant

关键词： Biomedical Image Fusion Biomedical Imaging Adaptive Exploratory Algorithm control point detection Biomedical Image Registration Mutual-Pixel-Count Heuristic Optimization Algorithm

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Automated Registration and Fusion of the Multi-Modality Retinal Images

Automated Registration and Fusion of the Multi-Modality Reti...

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40th Southeastern Symposium on System Theory (SSST 2008)

作者： Hua Cao Nathan Brener Hilary Thompson S. S. Iyengar Zhengmao Ye Department of Computer Science Louisiana State University Baton Rouge LA USA Electrical Engineering Department Southern University Baton Rouge LA USA

ISBN: (纸本)9781424418060

关键词： Biomedical Image Registration and fusion Adaptive Exploratory Algorithm control point detection Mutual-pixel-count Retinal Vasculature Extraction Heuristic Optimization

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