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Text recognition in bilingual machine printed image documents — Challenges and survey: A review on principal and crucial concerns of text extraction in bilingual printed images 10th

Text recognition in bilingual machine printed image document...

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International Conference on (ISCO) Intelligent systems and Control

作者： Shalini Puri Satya Prakash Singh Department of Computer Science Birla Institute of Technology Mesra Ranchi India

ISBN: (纸本)9781467378086

In this digital world, accurate text identification and recognition has become an important key area of image document analysis and processing. Textual data, ranging from simple to complex images along with language variations - mono, bi, tri or multilingual scripts, is identified and extracted. This paper is designed to focus the challenges and complex issues of text recognition in bilingual machine printed imaged documents. Major crucial factors are discovered and mentioned which become the bottlenecks in correct and accurate recognition. With this, a hierarchical structure depicting three Classification Schemes (CS) A, B and C of bilingual printed imaged document is shown, where A, B and C are related to the content form, image mining and language or script determination. Some loopholes of OCR working are also discussed. To analyze the existing algorithms and methods, a survey is presented to focus on their critical issues, proposed solutions along with constraints and errors found during text processing. It leads to find out the shortcomings and limitations of different methods. Various specifications and factors found from the techniques are also shown as their characteristics and are compared relatively to distinguish them. It is observed that most of the existing methods are based on the classification schemes CS A-A1 and C-C1 and C2 and are designed for the script identification with 300 dpi gray scale image using SVM classifier.

关键词： Two dimensional displays Manganese

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Zero resource anti-spoofing detection for unit selection based synthetic speech using image spectrogram artifacts

Zero resource anti-spoofing detection for unit selection bas...

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Asia-Pacific Signal and Information processing Association Annual Summit and Conference (APSIPA)

作者： Su Jun Leow Eng Siong Chng Chin-hui Lee Nanyang Technological University Singapore Georgia Institute of Technology USA

ISBN: (纸本)9781509024018

Synthesized speech poses a serious threat to speaker verification systems, which is aggravated by speech synthesis systems becoming more freely available and easily adaptable to a target speaker. This motivated research into synthetic speech detection to circumvent the threat. Although current algorithms are effective in the detection of HMM-based speech synthesizers, unit selection based speech synthesizers remain a serious threat due to its ability to generate spoofing speech which easily overcame existing detectors. Current error rates for their detection is a lot higher than that obtained for other spoofing methods. This paper proposes a detection algorithm to counter unit selection based synthesis speech. It is free of training and exploits presence of artifacts in image spectrogram to perform detection. To the best of our knowledge, this is the first attempt targeted for unit selection based synthesis speech. Experimental results show the effectiveness of the proposed approach.

关键词： Speech Spectrogram Synthesizers Speech synthesis Hidden Markov models Vocoders Feature extraction

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A novel shadow removal algorithm using Niblack segmentation in satellite images

A novel shadow removal algorithm using Niblack segmentation ...

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International Conference on Communication systems and Networks (ComNet)

作者： Geethu Vijayan S. R. Reshma F. E. Dhanya S. Anju Gayathri R. Nair R. P. Aneesh Mohandas College of Engineering And Technology Kerala University Anad Kerala India Mohandas College of Engineering and Tecnnotoqy Kerala University Anad Kerata India IHRd Regional Centre Trivandrum Kerala India

ISBN: (纸本)9781509033508

Shadow is formed by the interaction of light with object. Effect of shadow is very crucial in the case of satellite image processing. Roads, buildings, trees etc are detected for various applications. But the interference of shadow makes mismatching of these objects. Several algorithms are being developed to detect and reconstruct the shadow region. This paper presents a Shadow detection technique based on Niblack segmentation. Niblack segmentation gives better shadow regions compared to Otsu's thresholding method and Sauvola based thresholding. Reconstruction of the shadow region is done by the Bayesian classifier. This classifier generate a training vector and reconstruct non shadow region from shadow region. Posterior probability is determined to reconstruct the non shadow image intensity level. This algorithm is successfully tested with VHSR images.

关键词： image reconstruction image segmentation Satellites Filtering image edge detection Bayes methods Histograms

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Fundamental Matrix Estimation Based on Improved Genetic Algorithm

Fundamental Matrix Estimation Based on Improved Genetic Algo...

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International Conference on Intelligent Human-Machine systems and Cybernetics, IHMSC

作者： Ying Zhang Lan Zhang Changyin Sun Guifeng Zhang School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China China Southern Power Grid Electric Power Research Institute Guangzhou China

ISBN: (纸本)9781509007691

Fundamental matrix estimation is the key technology in 3D reconstruction and widely used in many aspects in computer vision. In this paper, a global search genetic algorithm combining with a local search hill climbing algorithm is proposed to optimize MAPSAC algorithm for estimating fundamental matrix. The average distances between points and epipolar lines under noise and outliers are investigated with synthetic and real image feature point data respectively. The simulation results show proposed method is more robust to noise and outliers and can estimate fundamental matrix more precisely.

关键词： Estimation Genetic algorithms Robustness Geometry Signal processing algorithms Noise level Three-dimensional displays

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Investigation and performance analysis of OpenVX optimizations on computer vision applications

Investigation and performance analysis of OpenVX optimizatio...

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International Conference on Control, Automation, Robotics and Vision

作者： Djamila Dekkiche Bastien Vincke Alain Merigot SATIE Univ. Paris-Sud CNRS Universite Paris-Saclay 94235 Cachan France IRT SystemX 91120 Palaiseau France SATIE Univ. Paris-Sud CNRS Universite Paris-Saclay 94235 Cachan France

ISBN: (纸本)9781509035502

The development of Advanced Driver Assistance systems (ADAS), such as pedestrian detection, requires real-time update rates at high image resolution. Hopefully, heterogeneous architectures with high computing performance have been developed for this purpose. To benefit from this hardware performance, different programming languages and acceleration frameworks have been developed. OpenVX framework provides a graph-based execution model to program image processing algorithms on heterogeneous platforms. In this work, we investigate OpenVX optimizations for computer vision applications. We examine how this framework responds to different data access patterns. We test three important optimizations of OpenVX: kernels merge, data tiling and parallelization via OpenMP. The contribution and the impact of each optimization on different data access pattern are explained.

关键词： images computer vision advanced driver assistance systems (ADAS) computational performance image processing algorithm Frameworks Access to Information information retrieval parallelization

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FPGA based Hardware Implementation of Automatic Vehicle License Plate Detection System

FPGA based Hardware Implementation of Automatic Vehicle Lice...

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International Conference on Advances in Computing, Communications and Informatics

作者： Surbhi Chhabra Himanshu Jain Sandeep Saini Department of Electronics and Communication Engineering The LNM Institute of Information Technology Jaipur (Raj.) India 302031

ISBN: (纸本)9781509020300

Automatic Vehicle License Plate Detection System (AVLPDS) is the extraction of vehicle license plate information from an image. Besides the safety aspects this system is used in many applications, viz. electronic payment systems, freeway, arterial monitoring systems for traffic surveillance etc. The purpose of this paper is to present the FPGA algorithmic model of most efficient algorithm among three algorithms: Edge-based, Connected-Component based and Histogram based. Each approach is analyzed on the basis of precision and recall rates to determine the success of each approach. After comparison, we can say Histogram based approach has an advantage of being simple and thus faster. Therefore, in this paper, we have used Histogram based Edge processing approach to detect the license plate and presented the FPGA implementation of AVLPDS for the same. The whole system is implemented using MATLAB Simulink and Xilinx System Generator (XSG). Use of XSG for image processing effectively reduces the complexity in structural design and contributes for hardware co-simulation. The accuracy of the algorithm is checked for different sets of input images and significant performance improvement has been found, thereby performing an optimal FPGA-based hardware implementation of AVLPDS.

关键词： Automatic Vehicle License Plate Detection System MATLAB Simulink Xilinx System generator VIVADO HLS FPGA ZedBoard image processing

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A new inspection method for bridge deformation

International Journal of Signal Processing, Image Processing...

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International Journal of Signal processing, image processing and Pattern Recognition 2016年第7期9卷 49-64页

作者： Cai, Bo Liu, Zhigui Wang, Junbo Zhu, Yuyu Southwest University of Science & Technology MianyangSichuan621010 China China Academy of Engineering Physics MianyangSichuan621000 China

The deformation of the location of structural systems is an important step to predict the performance of the system under different conditions. In bridges, the plastic deformations generally occur over a long-span beam after years of service. To improve the detection accuracy and stability of bridge deformation, in this paper, we proposed a new deformation inspecting framework. The total procedure of our algorithm may be concluded as the following three aspects. Firstly, because of the beams of bridges are very long, to improve the resolution of images, we divided the acquiring of the bridge beam image into a sequential images. Secondly, the sequential images are proposed with character point extraction, image stitching, image segmentation, and the calculation of the bridge deformation. Finally, the calculated deformation was compared with the experimental results. According to the experiments on the real bridges and the simulating model, the results indicated that our algorithm may improve the detection accurate to a large extent. At the same time, the proposed algorithm is more flexible than the former proposed algorithms. © 2016 SERSC.

关键词： image segmentation

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提高图像亮度的子像素着色算法

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激光与光电子学进展 2016年第9期53卷 96-105页

作者：冯俊严利民夏明治上海大学机电工程与自动化学院上海200072 上海大学微电子研究与开发中心上海200072

介绍了两种RGBW排列结构的子像素着色算法,既保证了与传统RGB传统排列一样的分辨率,又提高了图像的亮度。图像处理过程包含两个算法:RGB到RGBW的转化算法和RGBW的子像素着色算法。RGB到RGBW的转化算法使图像获得新的RGBW数据,可在保证原... 详细信息

介绍了两种RGBW排列结构的子像素着色算法,既保证了与传统RGB传统排列一样的分辨率,又提高了图像的亮度。图像处理过程包含两个算法:RGB到RGBW的转化算法和RGBW的子像素着色算法。RGB到RGBW的转化算法使图像获得新的RGBW数据,可在保证原RGB排列图像的色彩饱和度的同时提高图像的亮度,RGBW的子像素着色算法使图像更加逼真柔和,减少锯齿感。仿真结果表明,所提出的RGBW排列及着色算法可明显提高图像亮度。

关键词：成像系统图像亮度子像素着色算法 RGB RGBW

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Person Tracking and Gesture Recognition in Challenging Visibility Conditions Using 3D Thermal Sensing

Person Tracking and Gesture Recognition in Challenging Visib...

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IEEE International Symposium on Robot and Human Interactive Communication

作者： Ariel Kapusta Patrick Beeson TRACLabs Inc.

ISBN: (纸本)9781509039302

Many existing person tracking systems are challenged by non-laboratory scenarios, including variable lighting conditions, rain, smoke, tracking distance, and tracking speed. We provide evidence that by using a 3D thermal sensor, a person can be tracked in three dimensions with high success using very simple tracking methods, in many of the challenging lighting conditions and other weather conditions that confound other systems. In support of our claim, we present the PROWL (Perception for Robotic Operation over Widespread Lighting) sensor system, which uses thermal stereo image processing and on-board sensor processing to perform person tracking and gesture recognition. PROWL, using only ICP-based point matching algorithms, obtains 100% person tracking success at 20 frames per second out to 13 meters and zero false-positive/false-negative gesture recognition within 7 meters in all tested scenarios, which includes a sunny outdoor environment, a nighttime outdoor environment, a blackout indoor environment, and a whiteout smoke-filled indoor environment.

关键词： Gesture recognition Persons Stereo image processing tracking Lighting Three Dimensions Claim

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High-fidelity simulation for evaluating robotic vision performance

High-fidelity simulation for evaluating robotic vision perfo...

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IEEE/RSJ International Conference on Intelligent Robots and systems

作者： John Skinner Sourav Garg Niko Sunderhauf Peter Corke Ben Upcroft Michael Milford ARC Centre of Excellence for Robotic Vision Queensland University of Technology (QUT) Brisbane Australia

ISBN: (纸本)9781509037636

Robotic vision, unlike computer vision, typically involves processing a stream of images from a camera with time varying pose operating in an environment with time varying lighting conditions and moving objects. Repeating robotic vision experiments under identical conditions is often impossible, making it difficult to compare different algorithms. For machine learning applications a critical bottleneck is the limited amount of real world image data that can be captured and labelled for both training and testing purposes. In this paper we investigate the use of a photo-realistic simulation tool to address these challenges, in three specific domains: robust place recognition, visual SLAM and object recognition. For the first two problems we generate images from a complex 3D environment with systematically varying camera paths, camera viewpoints and lighting conditions. For the first time we are able to systematically characterise the performance of these algorithms as paths and lighting conditions change. In particular, we are able to systematically generate varying camera viewpoint datasets that would be difficult or impossible to generate in the real world. We also compare algorithm results for a camera in a real environment and a simulated camera in a simulation model of that real environment. Finally, for the object recognition domain, we generate labelled image data and characterise the viewpoint dependency of a current convolution neural network in performing object recognition. Together these results provide a multi-domain demonstration of the beneficial properties of using simulation to characterise and analyse a wide range of robotic vision algorithms.

关键词： robot vision Cameras images high fidelity object recognition image data Simulation models Environments simulating Lighting

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