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Automatic Construction of 3-D Building Model From Airborne LIDAR Data Through 2-D snake algorithm

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2015年第1期53卷 3-14页

作者： Yan, Jianhua Zhang, Keqi Zhang, Chengcui Chen, Shu-Ching Narasimhan, Giri Amazon Com Inc Seattle WA 98144 USA Florida Int Univ Dept Environm Studies Miami FL 33199 USA Florida Int Univ Int Hurricane Res Ctr Miami FL 33199 USA Univ Alabama Birmingham Dept Comp & Informat Sci Birmingham AL 35294 USA Florida Int Univ Distributed Multimedia Informat Syst Lab Sch Comp & Informat Sci Miami FL 33199 USA Florida Int Univ Sch Comp & Informat Sci Miami FL 33199 USA

The snake algorithm has been proposed to solve many remote sensing and computer vision problems such as object segmentation, surface reconstruction, and object tracking. This paper introduces a framework for 3-D building model construction from LIDAR data based on the snake algorithm. It consists of nonterrain object identification, building and tree separation, building topology extraction, and adjustment by the snake algorithm. The challenging task in applying the snake algorithm to building topology adjustment is to find the global minima of energy functions derived for 2-D building topology. The traditional snake algorithm uses dynamic programming for computing the global minima of energy functions which is limited to snake problems with 1-D topology (i.e., a contour) and cannot handle problems with 2-D topology. In this paper, we have extended the dynamic programming method to address the snake problems with a 2-D planar topology using a novel graph reduction technique. Given a planar snake, a set of reduction operations is defined and used to simplify the graph of the planar snake into a set of isolated vertices while retaining the minimal energy of the graph. Another challenging task for 3-D building model reconstruction is how to enforce different kinds of geometric constraints during building topology refinement. This framework proposed two energy functions, deviation and direction energy functions, to enforce multiple geometric constraints on 2-D topology refinement naturally and efficiently. To examine the effectiveness of the framework, the framework has been applied on different data sets to construct 3-D building models from airborne LIDAR data. The results demonstrate that the proposed snake algorithm successfully found the global optima in polynomial time for all of the building topologies and generated satisfactory 3-Dmodels for most of the buildings in the study areas.

关键词： Light detection and ranging (LIDAR) snake algorithm topology

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Contour tracking using a knowledge-based snake algorithm to construct three-dimensional pharyngeal bolus movement

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DYSPHAGIA 1999年第4期14卷 219-227页

作者： Chang, MW Lin, E Hwang, JN Univ Washington Dept Rehabil Med Seattle WA 98195 USA Univ Washington Dept Elect Engn Seattle WA 98195 USA

Videofluorography (VFG) using a barium-mixed bolus is in wide clinical use for assessing patients with swallowing disorders. VFG is usually done with both lateral (LA) and anterior-posterior (AP) views, most commonly in two separate sittings. A real-time, three-dimensional (3-D) representation of the evolution of a pharyngeal bolus and its volumetric information can potentially help clinicians analyze and visualize the kinematics of swallowing, dysphagia, and compensatory therapeutic strategies. Active contour models, also known as "snakes," have been used to solve various image analysis and computer vision problems. We applied a snake algorithm to automate in part the contour tracking and reconstruction of VFG images to visualize and quantitatively analyze the 3-D evolution of a pharyngeal bolus. To improve the accuracy of the snake search, we provided the additional "knowledge" of the pharyngeal image itself, which served as an extra constraint to push the snake curve toward the desired contour. VFG of pharyngeal bolus transport in a normal subject was recorded by using barium-mixed boluses (viscosity: 185 centipoise, density: 2.84 g/cc) with volumes of 5, 10, and 20 ml, The resulting LA and AP video images were digitally captured and matched frame by frame. The knowledge-based snake search algorithm was used to generate snake points to satisfy both internal (i.e., smoothness) and external (i.e., boundary fitting) constraints. Using these snake points, we traced the 3-D bolus movement at each time instant, assuming elliptic geometry in the cross-section of the pharyngeal bolus. By concatenating the 3-D images for each time instant, we developed a 3-D movie representing pharyngeal bolus movement. The efficiency, reproducibility, and accuracy of this algorithm in tracing pharyngeal bolus boundaries and estimating front/tail velocities were assessed and found satisfactory. We conclude that 3-D pharyngeal bolus movement can be traced both accurately and efficiently by

关键词： pharyngeal bolus transport contour tracking snake algorithm deglutition deglutition disorders

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The Implementation of Using P-P-C Filter to Balloon snake algorithm

The Implementation of Using P-P-C Filter to Balloon Snake Al...

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IEEE 2nd International Symposium on Next-Generation Electronics (ISNE)

作者： Tsui, Ta-Shan Yu, Shyr-Shen Lin, Shi-Hwang Lin, Jr-Luen Change, Huang-Chieh Hsu, Chih-Yu Natl Chung Hsing Univ Dept Comp Sci & Engn Taichung 402 Taiwan Natl Chung Hsing Univ Dept Appl Math Taichung 402 Taiwan ChaoYang Univ Technol Dept Informat & Commun Engn Taichung Taiwan

ISBN: (纸本)9781467330374;9781467330367

Using balloon snake algorithm to get the contour in an image, the contour will stay on the inner darker place (that is in the relatively minimum energy) of the image. To solve this problem, we usually use median filter or Gaussian filter as the tool of softening brightness of the image. These two filters will blur the edges of the object, thus increase the difficulty to find the real contour of the object. Papari, Petkov and Campisi propose an algorithm (P-P-C filter) to soften the internal part of an image and strengthen the edge of the objects in the image. When we use balloon snake algorithm to process an image which relative contrast is not obvious, using P-P-C filter as the pre-process tool is still easier to identify the contour of the object of image than using median filter and Gaussian filter. In this paper, we use an example to illustrate that using P-P-C filter then use balloon snake algorithm to find the contour of an object is better than direct use balloon snake algorithm, using median filter then use balloon snake algorithm, and using Gaussian filter then use balloon snake algorithm to find the contour of an object.

关键词： snake algorithm balloon snake algorithm P-P-C filter median filter Gaussian filter

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Enhanced snake algorithm using the proximal edge search method

Enhanced snake algorithm using the proximal edge search meth...

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International Conference on Computational Science and Its Applications (ICCSA 2007)

作者： Cha, JeongHee Kim, GyeYoung Soongsil Univ Informat & Media Inst Sch Comp Sangdo 5 Dong Seoul South Korea

ISBN: (纸本)9783540744689

This paper proposes an enhanced snake algorithm using the proximal edge search method. The proposed algorithm adds a new energy term called "proximal edge search" to the existing greedy algorithm without any passive adjustment of weight. The new energy term is represented by the distance between the snake point and the edge when there is a proximal edge. This modified algorithm could improve the accuracy by acquiring the detailed contour of complex objects and actively resolve the passive determination of weight. The validity of the proposed method was proven through experiments.

关键词： proximal edge search snake algorithm greedy algorithm weight determination

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Post Processing of Breast Phantom MRI-156 Images Using snake algorithm

Post Processing of Breast Phantom MRI-156 Images Using Snake...

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5th International Conference on Computer Graphics, Imaging and Visualization (CGIV)

作者： Rahman, Wan Eny Zarina W. Abd. Ibrahim, Arsmah Abu Bakar, Zainab Mahmud, Rozi Salikin, Md Saion Manaf, Mazani Univ Teknol MARA Fac Informat Technol & Quantitat Sci Shah Alam 40450 Selangor Malaysia Univ Putra Malaysia Fac Med Serdang Malaysia Univ Teknol MARA Fac Hlth Sci Petaling Jaya Malaysia

ISBN: (纸本)9780769533599

Mammography is a known method for the early detection of breast cancer. However, the mammograms which are in black and white and in the shade of grey have some limitations in portraying the abnormalities. Image segmentation is a very crucial process in detecting abnormalities in computed radiography mammographic images. Active contours which are known as 'snake' are dynamic algorithms which can be used to perform the image segmentation. In order to test the applicability of the snake algorithm in performing segmentation, the breast phantom MRI-156 images are used. Only the breast phantom images at the exposures of 25 kV, 28 kV and 35 kV with milliampere (mAs) of 0.5 are considered. It is found that when the image is divided into four equal regions, the detection of abnormalities in the image is more effective as compared to the image processed as a whole.

关键词： Mammogram Segmentation snake algorithm Breast Phantom

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Human Motion Tracking Based on B-spline snake algorithm

Human Motion Tracking Based on B-spline Snake Algorithm

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3rd International Conference on Mechatronics and Intelligent Materials (MIM 2013)

作者： Wang, Qunlong Xian Univ Architecture & Technol Xian Shaanxi Peoples R China

ISBN: (纸本)9783037857106

A new method for tracking of moving human objects is presented. The developed algorithm is based on B-spline snake model. The snake algorithm accesses the object contour through minimizing the energy;the object contour in each frame is presented through three B-spline curve. This approach gets the change image with double thresholds image segmentation between the neighboring frames, it could detect moving human objects with high quality and locate objects approximately. The contour extracts from the last frame put at the approximate position as the B-spline snake model initialization. It accomplishes the tracking of moving human objects.

关键词： snake algorithm B-spline curve object abstraction human motion tracking

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A Distributed snake algorithm for Mobile Robots Path Planning with Curvature Constraints

A Distributed Snake Algorithm for Mobile Robots Path Plannin...

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IEEE International Conference on System, Man, and Cybernetic

作者： Cheng, Y. Jiang, P. Hu, Y. Fun Univ Bradford Sch EDT Bradford BD7 1DP W Yorkshire England Univ Bradford Sch Informat Bradford BD7 1DP W Yorkshire England

ISBN: (纸本)9781424423835

Environment Intelligence is becoming ubiquitous. Wireless sensor networks supported environment intelligence is providing an opportunity to service robot navigation to reduce the complexity of conventional centralized and on-board map-building, localization, path-planning and motion control, whilst superior performance can be expected. In terms of robot path planning in a dynamic environment, distributed environment intelligence can take into account both global and local perceptions for path generation and adaptation, which results in better predictability and more prompt reaction. This paper proposes a snake based and distributed path planning algorithm for robot navigation in an intelligent environment with distributed wireless visual sensors. Via communication links between sensors, segments of a path, as an elastic band from start position to goal position, interact each other to react to repulsive forces from obstacles whilst maintain compliance. However, the compliance has to be subject to the robot kinematic constraints and the elastic hand may change to rigid or even to a broken state. A state machine is then presented to manage the state switch and control over the network. Simulations and experiments showed that the proposed distributed snake scheme can adapt to dynamic changes in the environment and satisfy the kinematic curvature constraints for the whole path.

关键词： robot navigation distributed path planning curvature constraints environment intelligence snake algorithm

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A Wheel-based Side-view Car Detection using snake algorithm

A Wheel-based Side-view Car Detection using Snake Algorithm

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IEEE 6th International Conference on Information and Automation for Sustainability (ICIAFS)

作者： Vinoharan, Veerapathirapillai Ramanan, Amirthalingam Kodituwakku, Saluka R. Univ Jaffna Comp Unit Jaffna Sri Lanka Univ Jaffna Dept Comp Sci Jaffna Sri Lanka Univ Peradeniya Dept Comp Sci & Stat Peradeniya Sri Lanka

ISBN: (纸本)9781467319751;9781467319768

Car detection is a challenging research area where the appearance has various changes due to different models, poses, scales, lighting conditions, background, occlusion and various image sizes. Amidst these external challenging factors, car side-views have obvious and consistent characteristics in their structure such as wheels, oblique windows and bumpers, which provide crucial cues for detection. In this paper, we describe a novel side-view car detection technique which constructs an initial contour for the snake using the detection of wheels. Our approach is subdivided in to three stages: wheel detection, bounding box detection, and segmenting the car from its background. In the first step, we use Hough transformation to detect circles in an image and validate the wheels with a learnt visual vocabulary. In the second step, we construct an initial contour with the aid of the detected wheels and the width-to-height statistics of different types of cars. This initial contour forms the bounding box of the car. In the third step, the snake algorithm proceeds with the initial contour to fit the boundary closer to the car. Hence, the foreground, car, is separated from the background. We empirically evaluated our method on 100 side-view cars and the testing results shows that this approach has good performance.

关键词： Car detection Circular Hough Transform snake algorithm SURF Visual Vocabulary

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Adventitia segmentation in intravascular ultrasound images based on improved snake algorithm

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OPTIK 2021年 241卷 167175-167175页

作者： Wang, Yousheng Gao, Xue Wang, Yuting Sun, Jinge Beijing Univ Technol Beijing 100124 Peoples R China

Segmentation of coronary artery intravascular ultrasound (IVUS) images is the first step in assessing blood vessel morphology and detecting possible atherosclerotic lesions. To overcome the disadvantage of manual acquisition of initial contour in traditional snake algorithm and construction of external force only from gradient information, an improved snake algorithm is proposed for automatic outer membrane segmentation in intravascular ultrasound images. Firstly, we design a basic segmentation algorithm to automatically extract the approximate contour of the first frame, and this is iterated as the initial contour of the snake algorithm. Next, the extended structure tensor is combined with the snake algorithm to make it part of the external force of the snake algorithm, and then the curve is evolved to complete the segmentation. To verify the effectiveness of the proposed method, this paper not only shows the experimental results qualitatively, but also quantitatively measures the RMSE and RDD indices. Comparative experiments show that the proposed method not only has higher accuracy, but also has better timeliness.

关键词： Intravascular ultrasound images Segmentation snake algorithm Structure tensor

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Improved snake Optimization and Particle Swarm Fusion algorithm Based on AUV Global Path Planning

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JOURNAL OF MARINE SCIENCE AND ENGINEERING 2025年第4期13卷 796-796页

作者： Jiang, Haobo Kuang, Xinghong Shanghai Ocean Univ Coll Engn Sci & Technol Shanghai 201306 Peoples R China

An improved snake optimization algorithm (ISO) is proposed to obtain an effective and reliable three-dimensional path for an autonomous underwater vehicle (AUV) to navigate seabed barrier environments and ocean currents. First, a three-dimensional seafloor environment model, seafloor obstacles, and a model of a Lamb vortex current are constructed. Second, the designed mathematical framework for three-dimensional path planning comprehensively considers a variety of constraints such as sailing distance, path threat, sailing altitude, and optimized ocean current energy consumption. Finally, ISO diversifies the snake population's distribution space by implementing a good point set initialization approach, a Cauchy variation strategy to enhance the convergence accuracy, and a fusion particle swarm algorithm strategy to improve the convergence speed. To evaluate ISO's optimization performance, by minimizing the fitness value, the optimization outcomes are contrasted with those of five different algorithms. The experimental results show that the ISO algorithm can generate safe, low-energy, and path-optimal AUV navigation planning, which presents a novel effective approach for AUV path planning.

关键词： ocean currents autonomous underwater vehicle snake algorithm

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