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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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Object-detection with a varying number of eigenspace projections

Object-detection with a varying number of eigenspace project...

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International Conference on pattern recognition

作者： M. Reiter J. Matas Pattern Recognition and Image Processing Group Institute for Automation University of Technology Vienna Vienna Austria CVSSP School of EE IT and Mathematics University of Surrey Guildford Surrey UK

We present a method allowing a significant speed-up of the eigen-detection method (detection based on principle component analysis). We derive a formula for an upper bound on the class-conditional probability (or equivalently a lower bound on the Mahalanobis distance) on which detection is based. Often, the lower bound of Mahalanobis distance (MD) reaches a preset threshold after computation of only a few eigen-projections. In this case the computation of MD can be immediately terminated. Regardless of the precise value of MD, the detection hypothesis (object from class /spl Omega/ is detected) can be rejected. While provably obtaining results identical to the standard technique, we achieved a two- to three-fold speed-up in face detection experiments on images from the CMU database.

关键词： Face detection Upper bound Object detection Lips pattern recognition image processing Automation Mathematics Electronic switching systems Read only memory

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Vehicle Routing Problem with Time Windows using Hybrid Metaheuristic Dragonfly Algorithm and Variable Neighborhood Search: Work on Progress 11

Vehicle Routing Problem with Time Windows using Hybrid Metah...

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11th International Conference on Electrical Engineering, Computer Science and Informatics, EECSI 2024

作者： Yunita, Yunita Stiawan, Deris Rini, Dian Palupi Sriwijaya University Faculty of Computer Science Indonesia Sriwijaya University Intelligent System Research Group Faculty of Computer Science South Sumatera Palembang Indonesia Sriwijaya University Communication Network and Information Security Research Group Faculty of Computer Science South Sumatera Palembang Indonesia Sriwijaya University Image Processing Dan Pattern Recognition Laboratory Group Faculty of Computer Science South Sumatera Palembang Indonesia

ISBN: (纸本)9798350355314

One of the problems with Smart Transportation is the problem of cost and travel time. This problem is known as the Variable Routing Problem (VRP). In some real cases, in addition to considering route selection, there are limitations on the capacity and time period for the vehicle to serve each customer known as Time Windows, so VRP has developed into Variable Routing Problem with Time Windows (VRPTW). One way to solve VRPTW is to use metaheuristic methods. However, the metaheuristic method has a weakness, which are it can get stuck in local optimums and fail to find better global solutions. To overcome this, a combination with other methods or known as hybrid is needed. The formulation of this research problem is how to develop a Smart transportation model using a metaheuristic hybrid algorithm. The purpose of this study is to develop a Smart transportation model using a metaheuristic hybrid algorithm. The method used is to combine two metaheuristic algorithms, which are the Dragonfly Algorithm (DA) and the Variable Neighborhood Search (VNS). The result of this research is a new algorithm model which is a hybrid between DA and VNS. Through a combination of global exploration using DA and local exploitation using VNS, this algorithm is expected to be able to find a better solution and faster convergence in solving VRPTW problems © 2024 IEEE.

关键词： Travel time

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On the detection of individuals and vehicles on an airport's apron

On the detection of individuals and vehicles on an airport's...

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IEE International Conference on Visual Information Engineering (VIE 2005)

作者： Josep Aguilera Antequera Martin Kampel Vienna University of Technology Institute of Computer Aided Automation Pattern Recognition and Image Processing Group Favoritenstr.9 183-2 A-1 040 Vienna Austria

This paper gives a robust motion detection and tracking solution for a video surveillance application on an airport's apron. As an outdoor application, the system must be capable of adapting to a wide range of weather conditions and illumination changes, furthermore, the achromaticity of the scene and the presence of occlusions in the tracking process are issues considered in the selection of the motion detector and tracking system respectively. We propose an adapted mixture of Gaussiani model with RGB colour normalisation to detect mobile objects in the scene and a region tracking method based on significant mobile object features to track individuals and vehicles on the selected airport's apron. The performance of the proposed motion detector is evaluated using pixel-based performance metrics and compared with other existing methods. The capability of the application to handle partial occlusions is tested on the region tracker.

关键词： Tracking Airports Surveillance Adaptation models Visualization Motion detection Atmospheric modeling

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Perceptual prediction for bionically inspired autonomous agents

Perceptual prediction for bionically inspired autonomous age...

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AFRICON Conference

作者： Clemens Muchitsch Alexander Wendt Klaus Doblhammer Dietmar Bruckner Jana Machajdik Institute of Computer Technology Vienna University of Technology Vienna Austria Institute of Computer Aided Automation Pattern Recognition and Image Processing Group Vienna University of Technology Vienna Austria

To manage the increasing volume of data per time unit, achievements in information processing and artificial intelligence were made. But still the complex processes of human perception and scenario recognition are not fully understood and still far from implementation in technical applications. The contribution of this article to the field of cognitive automation is the concept of prediction for perceptual- and scenario-recognition frameworks. It is a model where prediction originates from neuro-psychoanalytical theories. Inspired by experience-based planning, which is used by the psychoanalytical decision unit, the prediction of possible outcomes from scenarios can be used for proactive acting. It results in a higher detection rate and a faster performance for recognition-units. This first implementation shows the possibilities of the concept and gives an outlook of the performance as soon as the system is fully integrated in the decision-unit.

关键词： Humans Knowledge based systems Conferences TV Educational institutions Brain modeling Decision making

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Ancient document analysis based on text line extraction

Ancient document analysis based on text line extraction

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International Conference on pattern recognition

作者： Florian Kleber Robert Sablatnig Melanie Gau Heinz Miklas Pattern Recognition and Image Processing Group Institute of Computer Aided Automation University of Technology Vienna Vienna Austria Institute for Slavonic Studies University of Technology Vienna Vienna Austria

ISBN: (纸本)9781424421749

In order to preserve our cultural heritage and for automated document processing libraries and national archives have started digitizing historical documents. In the case of degraded manuscripts (e.g. by mold, humidity, bad storage conditions) the text or parts of it can disappear. The remaining parts of the text can be segmented and the ruling can be extrapolated with the a priori knowledge. Since the ruling defines the position of the text within a page, it can be used for layout analysis and as a basis for the enhancement of the readability. Furthermore, information about the scribe (hand) of the manuscript, its spatiotemporal origin can be gained by analyzing the ruling. This paper presents an algorithm for ruling estimation of Glagolitic texts based on text line extraction and is suitable for degraded manuscripts by extrapolating the baselines with the a priori knowledge of the ruling. The algorithm was tested on 30 pages of the Missale Sinaiticum and the evaluation was based on visual criteria.

关键词： Text analysis Degradation Algorithm design and analysis image segmentation image analysis Spatiotemporal phenomena Information analysis Data mining Software libraries Clustering algorithms

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Visual Surveillance for Aircraft Activity Monitoring

Visual Surveillance for Aircraft Activity Monitoring

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Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance

作者： D. Thirde M. Borg J. Ferryman V. Valentin F. Fusier F. Bremond M. Thonnat J. Aguilera M. Kampel Computational Vision Group University of Reading UK ORION Team I.N.R.I.A. Sophia Antipolis France Pattern Recognition and Image Processing Group University of Technology Vienna Austria

This paper presents a visual surveillance system for the automatic scene interpretation of airport aprons. The system comprises two modules - scene tracking and scene understanding. The scene tracking module, comprising a bottom-up methodology, and the scene understanding module, comprising a video event representation and recognition scheme, have been demonstrated to be a valid approach for apron monitoring

关键词： Surveillance Aircraft Monitoring Layout Tracking Motion detection Airports Vehicles image motion analysis Computer vision

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Background mosaic from egomotion

Background mosaic from egomotion

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International Conference on pattern recognition

作者： R. Megret C. Saraceno W. Kropatsch École Normale Supérieure de Lyon Lyon France Starlab NV Brussels Belgium Pattern Recognition and Image Processing group University of Technology Vienna Vienna Austria

ISBN: (纸本)0769507506

A framework is presented that produces the mosaic corresponding to the background object of an image sequence. It is based on the dominant motion assumption, which states that the background has a parametric motion and occupies the main part of the images. The foreground objects are localised by their different motion. This localisation is computed together with the background motion in an iterative method. The regions corresponding to the background are then pasted onto the mosaic using classic methods adapted to object elimination or a new mosaicking method based on a striping that takes the foreground objects localisation into account.

关键词： image segmentation Pixel Parametric statistics pattern recognition image processing image sequences Iterative methods Video sequences Buildings Motion segmentation

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Contrast Enhancement in Multispectral images by Emphasizing Text Regions

Contrast Enhancement in Multispectral Images by Emphasizing ...

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IAPR International Workshop on Document Analysis Systems, DAS

作者： Martin Lettner Florian Kleber Robert Sablatnig Heinz Miklas Pattern Recognition and Image Processing Group Institute for Computer Aided Automation University of Technology Vienna Vienna Austria Institute for Slavonic Studies University of Technology Vienna Vienna Austria

This paper deals with the enhancement of the readability in historic texts written on parchment. Due to mold, air, humidity, water, etc. parchment and text are partially damaged and consequently hard to read. In order to enhance the readability of the text, the manuscript pages are imaged in different spectral bands ranging from 360 to 1000 nm. The readability enhancement is based on a spectral and spatial analysis of the multivariate image data by multivariate spatial correlation. The main advantage of the method is that especially the text regions are enhanced which is provided by generating a mask image. This mask is based on the automatic reconstruction of the ruling scheme of the text pages. The method is tested on two medieval Slavonic manuscripts written on parchment.

关键词： Multispectral imaging Principal component analysis Degradation image analysis Humidity Spectral analysis Hyperspectral imaging Text analysis pattern analysis pattern recognition

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A comparision of Model-based methods for knee cartilage segmentation

A comparision of Model-based methods for knee cartilage segm...

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2nd International Conference on Computer Vision Theory and Applications, VISAPP 2007

作者： Cheong, J. Faggian, N. Langs, G. Suter, D. Cicuttini, F. Dept. of Electrical Dept. of Computer Systems Engineering Monash University Australia Clayton School of Information Technology Monash University Australia Institute for Computer Graphics and Vision Graz University of Technology Austria Pattern Recognition and Image Processing Group Vienna University of Technology Austria Dept. of Epidemiology Dept. of Preventive Medicine Monash University Australia

Osteoarthritis is a chronic and crippling disease affecting an increasing number of people each year. With no known cure, it is expected to reach epidemic proportions in the near future. Accurate segmentation of knee cartilage from magnetic resonance imaging (MRI) scans facilitates the measurement of cartilage volume present in a patient's knee, thus enabling medical clinicians to detect the onset of osteoarthritis and also crucially, to study its effects. This paper compares four model-based segmentation methods popular for medical data segmentation, namely Active Shape Models (ASM) (Cootes et al., 1995), Active Appearance Models (AAM) (Cootes et al., 2001), Patch-based Active Appearance Models (PAAM) (Faggian et al., 2006), and Active Feature Models (AFM) (Langs et al., 2006). A comprehensive analysis of how accurately these methods segment human tibial cartilage is presented. The results obtained were benchmarked against the current "gold standard" (cartilage segmented manually by trained clinicians) and indicate that modeling local texture features around each landmark provides the best results for segmenting human tibial cartilage.

关键词： Medical imaging

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