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2019 7th International Conference on Machinery,Materials and Computing Technology(ICMMCT 2019)

作者： Dong Fei Shaanxi Railway Institute

Computer vision technology has developed rapidly in the current computer world,and the processing methods for video images have also been significantly *** on the computer theory based on Marr,this paper discusses and studies the tracking of moving objects in *** the motion change of the monitored vehicle as an example,the Robert algorithm is used to track the changes of the vehicle during driving,and the multi-association template matching method is used to improve the accuracy of the *** is proved in the experiment that the algorithm in this paper has better precision in the tracking of the vehicle and can meet the current needs for tracking the moving target.

关键词： tracking algorithm image segmentation algorithm machine vision

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NIV-NGM - A Novel Non-invasive Blood Glucose Monitoring Method based on Near-infrared Videos

NIV-NGM - A Novel Non-invasive Blood Glucose Monitoring Meth...

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IEEE International Conference on Bioinformatics and Biomedicine

作者： Weijie Liu Guangyu Wang Anpeng Huang Ping Wang School of Software and Microelectronics Peking University Department of Computer Science and Technology Tsinghua University National Health Big-Data Institute Peking University

ISBN: (纸本)9781728118680

A Non-invasive blood Glucose Monitoring (NGM) method is desired for diabetes patients. Unfortunately, there is no practical NGM technique available for considering clinical accuracy requirements. One of the major causes is raised from the interferences of Environmental Background (EB) and Physiological Background (PB) noises. In this study, we propose a novel NGM method, called NIV-NGM. Based on the near-infrared video of a user's finger, NIV-NGM automatically separates the blood vessel and the background (other tissues) by an image segmentation algorithm and estimates the glucose level using features extracted from them. Compared with other NGM methods, NIV-NGM can differentiate the glucose-related information from the background, and also compensates for the measurement results due to the background noises. Clinical experimental results demonstrate that NIV-NGM is robust and immune from EB and PB noise influence, while can achieve the expected monitoring accuracy (Clarke (A) = 0.96).

关键词： Diabetes Non-invasive Blood glucose NIV-NGM Near-infrared video Blood Glucose Diabetes Mellitus blood glucose measurement image segmentation algorithm Blood Vessels Videotapes glucose level BACKGROUND Lead Noise BACKGROUND NOISE

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Highway Visibility Detection Method Based on Surveillance Video

Highway Visibility Detection Method Based on Surveillance Vi...

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International Conference on image, Vision and Computing (ICIVC)

作者： Ying Meng Hongtao Wu Shanxi Transportation Technology Research & Development Co. Ltd Taiyuan China

ISBN: (纸本)9781728123264

Low visibility weather has seriously affected daily traffic management and safety of life and property. Aiming at the problem that highway in low visibility environment is prone to traffic accidents, a highway visibility detection method based on video surveillance is proposed, and the surveillance video data of each section are analyzed. Based on the traditional dark channel prior, the highway visibility detection method converted the surveillance video frame into gray image, and extracted the air transmittance and atmospheric light value contained in the surveillance image by combining the adaptive guided filtering algorithm and quadtree image segmentation algorithm. Then based on the visibility calculation model, the visibility distance of the road was estimated according to the actual distance and offset angle between the monitoring equipment and the detection object. The experimental results show that the optimized image processing method can solve the problems of low image clarity, color distortion, and poor scene adaptability. The detection of visibility error rate meets the accuracy requirements of highway visibility detection in China. Finally, a road real-time visibility detection and warning system is applied based on the corresponding early warning strategies of each visibility level.

关键词： Visibility detection Dark channel prior Transmittance Atmospheric light transmittance Freeway visibility level visibility low visibility Sight distance inspection methods grayscale images offset angle actual distance monitoring equipment image segmentation algorithm required precision Alarm Systems Traffic management

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Technology and application of intelligent driving based on visual perception

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CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY 2017年第3期2卷 126-132页

作者： Zhang, Xinyu Gao, Hongbo Xie, Guotao Gao, Buyun Li, Deyi Tsinghua Univ Informat Technol Ctr Beijing 100083 Peoples R China Tsinghua Univ State Key Lab Automot Safety & Energy Beijing 100083 Peoples R China Beijing Inst Technol Sch Software Beijing 100081 Peoples R China Inst Elect Engn China Beijing 100039 Peoples R China

The camera is one of the important sensors to realise the intelligent driving environment. It can realise lane detection and tracking, obstacle detection, traffic sign detection, identification and discrimination and visual simultaneous localisation and mapping. The visual sensor model, quantity and installation location are different on different intelligent driving hardware experimental platform as well as the visual sensor information processing module, thus a number of intelligent driving system software modules and interfaces are different. In this study, the software architecture of the autonomous vehicle based on the driving brain is used to adapt to different types of visual sensors. The target segment is extracted by the image segmentation algorithm, and then the segmentation of the region of interest is carried out. According to the input feature calculation results, the obstacle search is done in the second segmentation region, the output of the accessible road area. As driving information is complete, the authors will increase or reduce one or more visual sensors, change the visual sensor model or installation location, which will no longer directly affect the intelligent driving decision, they make the multi-vision sensors adapted to the requirements of different intelligent driving hardware test platforms.

关键词： robot vision sensors intelligent driving system software modules visual perception road vehicles intelligent transportation systems image sensors camera visual simultaneous localisation and mapping obstacle detection software architecture feature extraction object detection driving brain visual sensor model intelligent driving hardware test platforms image segmentation algorithm intelligent driving hardware experimental platform multivision sensors intelligent driving decision target segment installation location traffic engineering computing image segmentation SLAM (robots) intelligent driving environment visual sensor information processing module segmentation region traffic sign detection visual sensors

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Improving RANSAC-Based segmentation Through CNN Encapsulation 30

Improving RANSAC-Based Segmentation Through CNN Encapsulatio...

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30th IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Morley, Dustin Foroosh, Hassan Univ Cent Florida Orlando FL 32816 USA

ISBN: (纸本)9781538604571

In this work, we present a method for improving a random sample consensus (RANSAC) based image segmentation algorithm by encapsulating it within a convolutional neural network (CNN). The improvements are gained by gradient descent training on the set of pre-RANSAC filtering and thresholding operations using a novel RANSAC-based loss function, which is geared toward optimizing the strength of the correct model relative to the most convincing false model. Thus, it can be said that our loss function trains the network on metrics that directly dictate the success or failure of the final segmentation rather than metrics that are merely correlated to the success or failure. We demonstrate successful application of this method to a RANSAC method for identifying the pupil boundary in images from the CASIA-IrisV3 iris recognition data set, and we expect that this method could be successfully applied to any RANSAC-based segmentation algorithm.

关键词： Metronidazole image segmentation algorithm segmentation segmentation encapsulating LOSS FUNCTION encapsulation iris recognition

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Assessing image segmentation algorithms for Sky Identification in GNSS

Assessing Image Segmentation Algorithms for Sky Identificati...

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International Conference on Indoor Positioning and Indoor Navigation (IPIN)

作者： Gakne, Paul Verlaine Petovello, Mark Univ Calgary Schulich Sch Engn Dept Geomat Engn Posit Locat & Nav PLAN Grp Calgary AB T2N 1N4 Canada

ISBN: (纸本)9781467384025

In order to improve the accuracy of user's position solution using Global Navigation Satellite System (GNSS) in urban canyons, it is important to know whether a satellite's signal is obstructed by surrounding buildings. This can be accomplished by using an upward-facing camera and segmenting the image into sky and non-sky. This paper evaluates the Otsu, Mean Shift, Graph cut and HMRF-EM-image image segmentation algorithms for this purpose. Since some algorithms provide two or more categories, segmentation is followed by k-means clustering techniques to yield only two categories;sky and non-sky. The algorithms are tested using images taken using an upwardfacing camera at roughly the same locations in different weather conditions: cloudy and sunny. Result shows that, when images are appropriately adjusted, the Otsu method overcomes the three other algorithms in terms of the percentage of sky accurately segmented and is also more computationally efficient. Experiment was also perform in Calgary downtown to show the effect of segmentation on the GNSS accuracy. Results show that, when obstructed satellites are removed, the RMS of the residuals decreases significantly compare to when all satellites are used.

关键词： Global Navigation Satellite System image segmentation algorithm sky satellites images segmentation Root mean square

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Supervised Evaluation of Seed-Based Interactive image segmentation algorithms 20

Supervised Evaluation of Seed-Based Interactive Image Segmen...

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20th SYMPOSIUM ON SIGNAL PROCESSING, imageS AND COMPUTER VISION (STSIVA)

作者： Andrade, Fernanda Carrera, Enrique V. Univ Fuerzas Armadas ESPE Casilla 171-5-231B Sangolqui Ecuador

ISBN: (纸本)9781467394611

Extensive research has been conducted in an effort to evaluate methods and techniques for image segmentation. However, while most literature has focused on evaluating automatic and semi-automatic algorithms, works evaluating interactive segmentation algorithms are less numerous. Note that interactive segmentation can improve results by adding prior knowledge from users into the process. Although this user guidance improves segmentation results, it also makes difficult to conduct objective evaluations. For this reason, some works only present non-canonical evaluations. In this paper, we present an objective and empirical evaluation of seed-based interactive segmentation algorithms. We first compare popular metrics that are employed in image-segmentation evaluations in order to define which one reflects most accurately the performance of segmentation algorithms. Then, in the aim of presenting reproducible results, we introduce a novel seed-based user input dataset that extends the well-known GrabCut dataset. In addition, we evaluate and contrast four state-of-the-art interactive segmentation algorithms. The analysis of the results demonstrates that Jaccard coefficient and Precision-Recall curves provide a good insight into the performance of the evaluated algorithms. Finally, the GrabCut algorithm presents the most robust and useful segmentation among all the evaluated algorithms.

关键词： image segmentation interactive systems GrabCut algorithm GrabCut dataset Jaccard coefficient objective evaluations precision-recall curves seed-based interactive image segmentation algorithms seed-based user input dataset segmentation results semiautomatic algorithms supervised evaluation Accuracy algorithm design and analysis Databases image color analysis image segmentation Measurement Semantics image segmentation algorithm design and analysis image colour analysis interactive systems image segmentation algorithm Semantics segmentation Database segmentation Interactive

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A Pyramidal image segmentation algorithm

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JOURNAL OF COMMUNICATIONS TECHNOLOGY AND ELECTRONICS 2010年第12期55卷 1550-1560页

作者： Chochia, P. A.

The problem of image segmentation (division into homogeneous regions) basing on color and texture region differences is considered. A two-level hierarchical pyramidal segmentation algorithm is proposed for solution of this problem. The homogeneity criterion is the estimated adjacency of the image elements and regions in the combined color-texture feature space. A metric in this space is introduced and studied. The results are verified on a set of test images of different types. DOI: 10.1134/S1064226910120296

关键词： image segmentation algorithm image segmentation Color instrument transmitters Eigenvector pixel PROBLEM SOLUTION

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A Method of Two-Dimensional Otsu image Threshold segmentation Based on Improved Firefly algorithm

A Method of Two-Dimensional Otsu Image Threshold Segmentatio...

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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Chenhang Zhou Liwei Tian Hongwei Zhao Kai Zhao Department of Electronic Engineering Shenyang University Liaoning Information Integration Technology Engineering Research Center of Internet of things

ISBN: (纸本)9781479987313

In order to solve the problems in Two-Dimensional image threshold segmentation such as, time consuming, low accuracy and easy to produce false segmentation image, a novel image segmentation algorithm that combing improved Firefly algorithm with Two-Dimensional Otsu(2-D Otsu) is proposed. First of all, an improved Firefly algorithm is proposed considering the influence of the historical best position of group when updating the location of fireflies. Then, searching the optimal segmenting threshold by using image threshold segmentation method with Two-Dimensional Otsu based on improved Firefly algorithm. Finally, completing image segmentation by the optimal segmentation threshold. It is shown that good segmentation performance is achieved by the improved algorithm, which may not only shorten the run time and improve the quality of image segmentation effectively, but also be applied to the real-time processing of image segmentation.

关键词： image segmentation Firefly algorithm Historical best position Two-Dimensional Otsu Optimal threshold image segmentation Lampyridae image thresholding segmentation segmentation Runtime image segmentation algorithm

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RGB-D image segmentation BASED ON MULTIPLE RANDOM WALKERS

RGB-D IMAGE SEGMENTATION BASED ON MULTIPLE RANDOM WALKERS

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IEEE International Conference on image Processing

作者： Se-Ho Lee Won-Dong Jang Byung Kwan Park Chang-Su Kim School of Electrical Engineering Korea University Video Tech. Lab. SK Telecom

ISBN: (纸本)9781467399623

A novel RGB-D image segmentation algorithm is proposed in this work. This is the first attempt to achieve image segmentation based on the theory of multiple random walkers (MRW). We construct a multi-layer graph, whose nodes are superpixels divided with various parameters. Also, we set an edge weight to be proportional to the similarity of color and depth features between two adjacent nodes. Then, we segment an input RGB-D image by employing MRW simulation. Specifically, we decide the initial probability distribution of agents so that they are far from each other. We then execute the MRW process with the repulsive restarting rule, which makes the agents repel one another and occupy their own exclusive regions. Experimental results show that the proposed MRW image segmentation algorithm provides competitive segmentation performances, as compared with the conventional state-of-the-art algorithms.

关键词： Multiple random walkers segmentation Random walk RGB-D image segmentation Random walk Probability distribution image segmentation algorithm images Agents image segmentation adjacent nodes

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