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电子学报 2011年第1期39卷 64-69页

作者：黄波赵继印郑蕊蕊李敏吉林大学通信工程学院吉林长春130025 大连民族学院机电信息工程学院辽宁大连116600

仿射不变量特征提取方法已成为计算机视觉研究的重点课题之一.本文提出一种归一化直方图算法,该算法基于多尺度自卷积变换中密度函数的概念,研究归一化密度函数的方法,构建了从目标图像中提取直方图仿射不变量特征提取算法,实现了基于... 详细信息

仿射不变量特征提取方法已成为计算机视觉研究的重点课题之一.本文提出一种归一化直方图算法,该算法基于多尺度自卷积变换中密度函数的概念,研究归一化密度函数的方法,构建了从目标图像中提取直方图仿射不变量特征提取算法,实现了基于多尺度自卷积归一化直方图的仿射不变量模式识别.仿真实验表明,本算法对一定范围内的噪声,局部遮挡,照度及视角变化具有良好的适应性,特别是在多种环境下,其识别率优于多尺度自卷积和基于多尺度自卷积的其它直方图算法.

关键词：目标识别仿射不变特征归一化直方图多尺度自卷积

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Embedded neuromorphic vision for humanoid robots

Embedded neuromorphic vision for humanoid robots

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IEEE computer Society Conference on computer vision and pattern recognition Workshops (CVPRW)

作者： Chiara Bartolozzi Francesco Rea Charles Clercq Daniel B. Fasnacht Giacomo Indiveri Michael Hofstätter Giorgio Metta Italian Institute of Technology Genoa Italy University of Zurich ETH Zurich Zurich Switzerland Austrian Institute of Technology GmbH Wien Austria Università degli Studi di Genova Genoa Italy

We are developing an embedded vision system for the humanoid robot iCub, inspired by the biology of the mammalian visual system, including concepts such as stimulus-driven, asynchronous signal sensing and processing. It comprises stimulus-driven sensors, a dedicated embedded processor and an event-based software infrastructure for processing visual stimuli. These components are integrated with the existing standard machine vision modules currently implemented on the robot, in a configuration that exploits the best features of both: the high resolution, color, frame-based vision and the neuromorphic low redundancy, wide dynamic range and high temporal resolution event-based sensors. This approach seeks to combine various styles of vision hardware with sensorimotor systems to complement and extend the current state-of-the art.

关键词： Visualization Field programmable gate arrays Robot sensing systems Voltage control Feature extraction

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Performance improvement of the license plate recognition systems with algorithmic fusion approach

Performance improvement of the license plate recognition sys...

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IEEE Signal Processing and Communications Applications (SIU)

作者： Engin Tamer Burak Çizmeci Elektrik-Elektronik Mühendisliği Bölümü Işık Üniversitesi Istanbul Turkey

In this paper, we propose an algorithmic fusion approach for performance improvement of the license plate recognition (LPR) systems which is a very important research topic in computer vision and pattern recognition areas. Basically, the building blocks of LPR system is composed of locating the LP, character segmentation and character recognition stages. Character segmentation and recognition phases are well studied in the fields of image processing and pattern recognition and very robust solutions were proposed in the literature. However, the most important problem of the LPR systems is locating the pixel precise position of the LP inside the image. In our previous work, we proposed a horizontal scan method to locate the LP. In this paper, we propose a square detection based LP locating algorithm which also locates the two lined LPs. In order to design a robust stage for the locating plate block, we present a new approach that combines the dexterity of the two different LPR locating algorithms within algorithmic fusion framework. According to our experiments, we observe that the overall performance of the LPR system is increased by the proposed algorithmic fusion method.

关键词： Conferences pattern recognition Signal processing Algorithm design and analysis Robustness Image segmentation Licenses

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Character extraction in web image for text recognition

Character extraction in web image for text recognition

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International Conference on pattern recognition

作者： Bolan Su Shijian Lu Trung Quy Phan Chew Lim Tan Department of Computer Vision and Image Understanding Institute for Infocomm Research Singapore Department of Computer Science School of Computing National University of Singapore Singapore

ISBN: (纸本)9781467322164

Images with text are frequently used on Internet for different purposes. Automatic recognition of text from web images plays an important role on extraction and retrieval of web information. However, the web images are usually in low resolution with artifacts and special effects, which makes word recognition a challenge task even after the text has been localized. In this paper, we propose a robust text recognition technique to efficiently convert the web images into text format. The proposed technique first makes use of the L0 norm smoothing to increase the edge contrast of the input web images. The images are then binarized on each color channel. A connected component analysis is followed to identify the possible character components. Finally the character candidates are recognized by the OCR engine after skew correction. Extensive experiments have been conducted on the latest ICDAR 2011 robust reading competition dataset for born-digital text. The experimental results show the superior performance of our proposed technique.

关键词： Text recognition Image recognition Smoothing methods Optical character recognition software Robustness Image color analysis Testing

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Analysis of eye gaze pattern of infants at risk of autism spectrum disorder using Markov models

Analysis of eye gaze pattern of infants at risk of autism sp...

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IEEE Workshop on Applications of computer vision (WACV)

作者： David Alie Mohammad H. Mahoor Whitney I. Mattson Daniel R. Anderson Daniel S. Messinger Department of Electrical and Computer Engineering University of Denver Denver CO USA Department of Psychology University of Miami Coral Gables FL USA

This paper presents the possibility of using pattern recognition algorithms of infant gaze patterns at six months of age among children at high risk for an autism spectrum disorder (ASD). ASDs, which must be diagnosed by 3 years of age, are characterized by communication and interaction impairments which frequently involve disturbances of visual attention and gaze patterning. We used video cameras to record the face-to-face interactions of 32 infant subjects with their parents. The video was manually coded to determine the eye gaze pattern of infants by marking where the infant was looking in each frame (either at their parent's face or away from their parent's face). In order to identify infants ASD diagnosis at three years, we analyzed infant eye gaze patterns at six months. Variable-order Markov Models (VMM) were used to create models for typically developing comparison children as well as children with an ASD. The models correctly classified infants who did and did not develop an ASD diagnosis with an accuracy rate of 93.75 percent. Employing an assessment tool at a very young age offers the hope of early intervention, potentially mitigating the effects of the disorder throughout the rest of the child's life.

关键词： Variable speed drives Hidden Markov models Markov processes Context Data models Training Autism

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Shape detection by packing contours and regions

Shape detection by packing contours and regions

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作者： Zhu, QIhui University of Pennsylvania

学位级别：Ph.D.

Humans have an amazing ability to localize and recognize object shapes from natural images with various complexities, such as low contrast, overwhelming background clutter, large shape deformation and significant occlusion. We typically recognize object shape as a whole - the entire geometric configuration of image tokens and the context they are in. Detecting shape as a global pattern involves two key issues: model representation and bottom-up grouping. A proper model captures long range geometric constraints among image tokens. Contours or regions that are grouped from bottom-up often appear as half complete shapes that are easily recognizable. The main challenge arises from the representation gap between image and model: fragmented image structures usually do not correspond to semantically meaningful model parts. This thesis presents Contour Packing, a novel framework that detects shapes in a global and integral way, effectively bridging this representation gap. We first develop a grouping mechanism that organizes individual edges into long contours, by encoding Gestalt factors of proximity, continuity, collinearity, and closure in a graph. The contours are characterized by their topologically ordered 1D structures, against otherwise chaotic 2D image clutter. Used as integral shape matching units, they are powerful for preventing accidental alignment to isolated edges, dramatically reducing false shape detections in clutter. We then propose a set-to-set shape matching paradigm that measures and compares holistic shape configurations. Representing both the model and the image as a set of contours, we seek packing a subset of image contours into a complete shape formed by model contours. The holistic configuration is captured by shape features with a large spatial extent, and the long-range contextual relationships among contours. The unique feature of this approach is the ability to overcome unpredictable contour fragmentations. Computationally, set-to-set-matchin

关键词： computer vision object recognition shape perception object representation shape matching convex optimization

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Embedded Microscope vision Based Mechanical Platform for LED Wafer Automatic Inspection

Embedded Microscope Vision Based Mechanical Platform for LED...

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2011 3rd International Asia Conference on Informatics in Control, Automation and Robotics(CAR 2011)

作者： Xinyan Gao Ning Zhou Dakui Li Yuan Yue School of Software Dalian University of Technology School of Computer and Information Technology Beijing Jiaotong University School of Mathematics and Computer Science Institute Northwest University for Nationalities

In this paper,we propose a novel technique solution towards LED wafer defects automatic full inspection using neural network chip array to assure defect-free outgoing *** research intends to develop an automatic inspection system for defect pattern recognition in order to substitute human visual *** solution mainly includes a three degree-of-freedom precise mechanical positioning stage and an automatic robot arm working with an embedded microscope vision system.A built-in parallel neural network chip array acts as the recognition engine instead of traditional software ***,the mechanical motion control is also based on neural network *** solution will benefit greatly from hardware engine acceleration as for performance improvement.

关键词： LED,Automatic Inspection,Neural Network,Microscope vision,Mechanical Platform

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NeuFlow: A runtime reconfigurable dataflow processor for vision

NeuFlow: A runtime reconfigurable dataflow processor for vis...

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IEEE computer Society Conference on computer vision and pattern recognition Workshops (CVPRW)

作者： Clément Farabet Berin Martini Benoit Corda Polina Akselrod Eugenio Culurciello Yann LeCun Electrical Engineering Department Yale University New Heaven CT USA Courant Institute of Mathematical Sciences New York University New York NY USA

In this paper we present a scalable dataflow hardware architecture optimized for the computation of general-purpose vision algorithms - neuFlow - and a dataflow compiler - luaFlow - that transforms high-level flow-graph representations of these algorithms into machine code for neuFlow. This system was designed with the goal of providing real-time detection, categorization and localization of objects in complex scenes, while consuming 10 Watts when implemented on a Xilinx Virtex 6 FPGA platform, or about ten times less than a laptop computer, and producing speedups of up to 100 times in real-world applications. We present an application of the system on street scene analysis, segmenting 20 categories on 500 × 375 frames at 12 frames per second on our custom hardware neuFlow.

关键词： Tiles computer architecture Runtime Field programmable gate arrays Hardware Convolvers Feature extraction

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Resolving occlusion in multiframe reconstruction of deformable surfaces

Resolving occlusion in multiframe reconstruction of deformab...

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IEEE computer Society Conference on computer vision and pattern recognition Workshops (CVPRW)

作者： Appu Shaji Aydin Varol Pascal Fua Yashoteja Ankush Jain Sharat Chandran Computer Vision Laboratory EPF Lausanne Switzerland Indian Institute of Technology Bombay Indian Institute of Technology Bombay India

Occlusion is troublesome for almost all computer vision algorithms. To a certain extent, the difficulty is alleviated when multiple frames are given. On the other hand, when we consider the recovery of shapes of moving deformable objects, observed using a monocular camera, the problem appears difficult again. In this paper, we show a method that outperforms previous approaches to reconstruction when feature data is unavailable, perhaps due to occlusion. Our key intuition is that portions of the surface that are visible in some frame can be reliably reconstructed in that frame; further, the reliable portions can be stitched together to find even missing portions, much the way a human eye would hallucinate. Our techniques are based on optimization in Riemannian shape spaces, and is demonstrated on isometric surfaces without involving any kind of machine learning methods.

关键词： Shape Three dimensional displays Mathematical model Optimization Surface reconstruction Image reconstruction Deformable models

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Composite Script Identification and Orientation Detection for Indian Text Images

Composite Script Identification and Orientation Detection fo...

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International Conference on Document Analysis and recognition

作者： Shamita Ghosh Bidyut B. Chaudhuri Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

A major preprocessing step in a multi-script OCR is to identify the script type of the test document image. The published papers on script identification usually assume that the test image is in correct i.e. 0° orientation. But by mistake a document may be fed to the system in wrong orientation, say at an angle of nearly 180° or ±90°. In this method we propose a script identification method that works for unknown orientation for all 11 official Indian scripts. Here, we first find the skew and counter-rotate the document by the skew angle. This will lead to correct (0°) or upside down (180°) orientation. Then script identification is done by a multi-stage tree classifier using features invariant to 0°/180° orientation. Next we go to find the orientation of the image by a two class classifier for each script. Performance of the proposed method has been tested on a variety of documents and promising results have been obtained.

关键词： Reservoirs Support vector machines Accuracy Feature extraction pattern recognition Kernel

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