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IEEE International Conference on Intelligent Computer Communication and processing (ICCP)

作者： Catalin Golban Sergiu Nedevschi Computer Science Department Technical University Image Processing and Pattern Recognition Group Cluj-Napoca Romania

This paper proposes a novel method for detecting the moving vehicles in dynamic urban traffic scenes using a stereo camera. Relying on the fact that a set of feature points on a rigid 3D scene object are staying in a rigid 3D configuration, we propose to compute the relative motion between the camera and a moving object with an algorithm that follows from the visual odometry based motion estimation methods. Subtracting the camera motion we obtain the absolute object motion. Additionally we create a compact representation of the scene using superpixels computed from intensity and depth information. A graph-like structure is built, having superpixels as nodes and indicating neighboring relationships between adjacent superpixels. Objects are segmented using a fast region growing algorithm that considers as seeds the features used to compute the object motion.

关键词： Three-dimensional displays Visualization Computer vision Cameras Feature extraction Stereo vision image motion analysis

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Exponential image Enhancement in Daytime Fog Conditions

Exponential Image Enhancement in Daytime Fog Conditions

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17th International IEEE Conference on Intelligent Transportation Systems & The Asia-Pacific Council on Systems Engineering Conference 2014

作者： Mihai Negru Sergiu Nedevschi Radu Ioan Peter Image Processing and Pattern Recognition Group Computer Science DepartmentTechnical University of Cluj-Napoca head of the Image Processing and Pattern Recognition Group Computer Science DepartmentTechnical University of Cluj-Napoca Mathematics Department Technical University of Cluj-Napoca

The images captured in fog conditions have degraded contrast,that makes current image processing applications sensitive and error *** propose in this paper an efficient single image enhancement algorithm suitable for daytime fog conditions and based on an original mathematical model,for computing the atmospheric veil,that takes into account the variation in fog density to the *** model is inspired by the functions that appear in partition of unity in the differential geometry *** observing images captured in fog conditions,usually the fog has a very low density in front of the camera and this density has a non-linear increase with the distance,such that objects are no longer visible at greater *** using our mathematical model we are able to obtain superior reconstructions of the original fog-free image,when comparing to traditional *** advantage of our method is the ability to adapt the model in accordance to the density of the fog.A quantitative and qualitative evaluation is performed on both synthetic and real camera *** evaluation proves that our mathematical model is more suitable for image enhancement in both homogeneous and heterogeneous fog *** algorithm is able to perform image enhancement in real time for both color and gray scale images.

关键词： image Exponential image Enhancement in Daytime Fog Conditions

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A novel level set method for remote sensing image based on K-means

A novel level set method for remote sensing image based on K...

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2014 International Conference on Applied Mechanics, Mechatronics and Intelligent System, AMMIS 2014

作者： Xu, Er Jing Jia, Zhen Hong Wang, Lie Jun Hu, Ying Jie Yang, Jie College of Information science and engineering Xinjiang University Urumchi 830046 China Knowledge Engineering and Research Discovery Institute Auckland University of Technology Auckland New Zealand The Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9783038351757

Due to the characteristic of remote sensing image, we propose a novel method based on K-means algorithm also with the improved multi-phrase level set model. Comparing with the classical multi-phase C-V model, the improved model considers the region area information, gradient information and edge detection. Proper use of gradient information can overcome the inaccurate edge localization defects in image segmentation. The edge detection is used for keeping the boundary information better in the evolution process. For the reason of picking up the contour's convergent speed and enable the avoidance of trap. Four stages are constructed. Firstly, a median filtering is applied to smooth the original image and reduce parts of noise. Secondly, the usage of K-means algorithm gains more obvious differences of characteristics. Next, the reconstruction of gradient is obtained by using Sobel operator. Finally, segmentation result is achieved by using an improved method of multi-phase level set image segmentation. Experimental results show that the proposed approach has advantages in rapid and efficient application of remote sensing image segmentation. © (2014) Trans Tech Publications, Switzerland.

关键词： image segmentation

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Text-independent writer identification by feature fusion

Text-independent writer identification by feature fusion

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International Conference on Intelligent Control and Information processing (ICICIP)

作者： Yongjie Hu Wenming Yang Youbin Chen Department of Electronic Engineering of Tsinghua University Zhejiang University Research interests include digital image processing and computer vision Department of Electronic Engineering of Tsinghua University Research interests include digital image processing and pattern recognition

ISBN: (纸本)9781479936519

This paper explores text-independent writer identification by combining Bag of Features (BoF), contour-hinge and SIFT scales feature. The BoF method adopted differs from the common BoF approach for writer identification in that it extracts SIFT descriptors and uses Locality-constrained Linear Coding to get feature vector of each document. The Locality-constrained Linear Coding (LLC) tries to reconstruct each feature through locality constraint and has much more discriminative power than the common used Vector Quantization (VQ). Contour-hinge feature can capture orientation and curvature of the ink trace. Modification is made to the original contour-hinge to improve the identification rate. Besides, we also use SIFT scale information and integrate these three kinds of features together. Experiments are conducted the challenging ICDAR2013 writer identification contest dataset and dataset for "ICFHR2012 Writer Identification Contest, Challenge 1: Latin Documents". The experiment results show that the proposed BoF approach outperforms the common ones that adopt VQ, and after the integration, our method achieves the best result on the entire ICDAR2013 and ICFHR2012 dataset under soft evaluation.

关键词： Feature extraction Vectors Encoding image reconstruction Text analysis Educational institutions

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Automatic removal of externally attached fiducial markers in cone beam C-arm CT

Automatic removal of externally attached fiducial markers in...

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Workshops Bildverarbeitung fur die Medizin: Algorithmen - Systeme - Anwendungen, BVM 2014 - Workshop on image processing for Medicine: Algorithms - Systems - Applications, BVM 2014

作者： Berger, Martin Forman, Christoph Schwemmer, Chris Choi, Jang H. Müller, Kerstin Maier, Andreas Hornegger, Joachim Fahrig, Rebecca Pattern Recognition Lab FAU Erlangen-Nürnberg Germany Research Training Group 1773 Heterogeneous Image Systems Stanford University StanfordCA United States Stanford University StanfordCA United States Department of Radiology Stanford University StanfordCA United States

ISBN: (纸本)9783642541100

In computed tomography fiducial markers are frequently used to obtain accurate point correspondences for further processing. These markers typically cause metal artefacts, decreasing image quality of the subsequent reconstruction and are therefore often removed from the projection data. The placement of such markers is usually done on a surface, separating two materials, e.g. skin and air. Hence, a correct restoration of the occluded area is difficult. In this work six state-of-the-art interpolation techniques for the removal of high-density fiducial markers from cone-beam CT projection data are compared. We conducted a qualitative and quantitative evaluation for the removal of such markers and the ability to reconstruct the adjoining edge. Results indicate that an iterative spectral deconvolution is best suited for this application, showing promising results in terms of edge, as well as noise restoration. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Restoration

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Topological image Analysis and (Normalised) Representations for Plant Phenotyping

Topological Image Analysis and (Normalised) Representations ...

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International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)

作者： Ines Janusch Walter G. Kropatsch Wolfgang Busch Pattern Recognition and Image Processing Group Vienna University of Technology Vienna Austria Gregor Mendel Institute of Molecular Plant Biology Austrian Academy of Sciences Vienna Austria

This paper discusses the use of topological image analysis to derive characteristics needed in plant phenotyping. Due to certain features of root systems (deformation over time, overlaps of branches in a 2D image of the root system) a topological analysis is needed to correctly derive these characteristics. The advantages of such a topological analysis are highlighted in this paper and root phenotyping is presented as a new application for computational topology. Characteristics used in plant phenotyping that can be derived from root images using methods of topological image analysis are further presented. A Reeb graph based representation of root images is shown as an example for such a topological analysis. Based on a graph representation a new, normalised representation of root images is introduced.

关键词： image segmentation Level measurement Topology Length measurement Skeleton image analysis Soil

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Remote sensing image change detection based on minimum spanning tree clustering

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Guangdianzi Jiguang/Journal of Optoelectronics Laser 2014年第12期25卷 2417-2422页

作者： Hu, Xue-Mei Jia, Zhen-Hong Qin, Xi-Zhong Yang, Jie Kasabov, Nikola College of Information Science and Engineering Xinjiang University Urumuqi China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Knowledge Engineering and Discovery Research Institute Auckland University of Technology Auckland New Zealand

To obtain complementary information of difference image and gain a better change detection result, this paper proposes an unsupervised change detection algorithm. The technique is based on minimum spanning tree (MST) clustering. First of all, a normalized neighborhood ratio approach is adopted to obtain the difference image of two images acquired in the same geographical area at different moments. Then divide pixels into changed pixels, unchanged pixels and uncertain pixels according to gray difference histogram. Aiming at uncertain pixels, use minimum spanning tree algorithm twice to clustering: texture features and minimum spanning tree algorithm are used for first clustering, then calculate every clustering's average weight, and regarded first clustering results as nodes to calculate the minimum spanning tree again. Finally, on the basis of optimal objective function, the uncertain pixels belong to the two clusters: changed pixels and unchanged pixels. In this paper, the effectiveness of the algorithm is proved by numerical calculation. Mexico data accuracy is 99.01% and operation time is 8.49 s, Sardinia data accuracy is 98.62% and operation time is 8.49 s. Compared with the other three kinds of algorithms, the proposed algorithm can obtain higher detection accuracy and shorter running time.

关键词： Pixels

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Estimation of distribution algorithm for the Max-Cut problem

Estimation of distribution algorithm for the Max-Cut problem

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9th IAPR-TC-15 International Workshop on Graph-Based Representations in pattern recognition, GbRPR 2013

作者： De Sousa, Samuel Haxhimusa, Yll Kropatsch, Walter G. Vienna University of Technology Pattern Recognition and Image Processing Group Vienna Austria

ISBN: (纸本)9783642382208

In this paper, we investigate the Max-Cut problem and propose a probabilistic heuristic to address its classic and weighted version. Our approach is based on the Estimation of Distribution Algorithm (EDA) that creates a population of individuals capable of evolving at each generation towards the global solution. We have applied the Max-Cut problem for image segmentation and defined the edges' weights as a modified function of the L2 norm between the RGB values of nodes. The main goal of this paper is to introduce a heuristic for Max-Cut and additionally to investigate how it can be applied in the segmentation context. © 2013 Springer-Verlag.

关键词： image segmentation

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Structural cues in 2D tracking: Edge lengths vs. barycentric coordinates 1

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18th Iberoamerican Congress on pattern recognition, CIARP 2013

作者： Artner, Nicole M. Kropatsch, Walter G. Vienna University of Technology Pattern Recognition and Image Processing Group Vienna Austria

ISBN: (数字)9783642418273

ISBN: (纸本)9783642418266

Graph models offer high representational power and useful structural cues. Unfortunately, tracking objects by matching graphs over time is in general NP-hard. Simple appearance-based trackers are able to find temporal correspondences fast and efficient, but often fail to overcome challenging situations like occlusions, distractors and noise. This paper proposes an approach, where an attributed graph is used to represent the structure of the target object and multiple, simple trackers in combination with structural cues replace the costly graph matching. Thus, the strengths of both methodologies are combined to overcome their weaknesses. Experiments based on synthetic videos are used to evaluate two possible structural cues. Results show the superiority of the cue based on barycentric coordinates and the potential of the proposed tracking approach in challenging situations. © Springer-Verlag 2013.

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On the evaluation of graph centrality for shape matching

On the evaluation of graph centrality for shape matching

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9th IAPR-TC-15 International Workshop on Graph-Based Representations in pattern recognition, GbRPR 2013

作者： De Sousa, Samuel Artner, Nicole M. Kropatsch, Walter G. Vienna University of Technology Pattern Recognition and Image Processing Group Vienna Austria

ISBN: (纸本)9783642382208

Graph centrality has been extensively applied in Social Network Analysis to model the interaction of actors and the information flow inside a graph. In this paper, we investigate the usage of graph centralities in the Shape Matching task. We create a graph-based representation of a shape and describe this graph by using different centrality measures. We build a Naive Bayes classifier whose input feature vector consists of the measurements obtained by the centralities and evaluate the different performances for each centrality. © 2013 Springer-Verlag.

关键词： Graphic methods

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