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检索条件"任意字段=2nd International Conference on Computer Vision and Image Processing, CVIP 2017"

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Raindrop Detection Algorithm for ADAS 2

Raindrop Detection Algorithm for ADAS

引用

2nd IEEE international conference on Recent Trends in Electronics, Information and Communication Technology (RTEICT)

作者： Asundi, Pavan Kumar Geetha, K. S. RV Coll Engn ECE Dept Bengaluru India

ISBN: (纸本)9781509037049

vision based advance driver assistance system (ADAS) completely rely on the images captured by the vehicle bound camera. vision based ADAS also referred as computer vision based ADAS depends on clear images from surroundings for its algorithm implementation. If the images are hampered from external weather conditions such as rain or fog, the ADAS functionalities are affected. In general, checking the image, whether it is free from raindrop occlusions is one of the steps in the pre-processing, as clear, noise free images are required for ADAS algorithm deployments, which would enhance the ADAS functionalities. In ADAS, generically raindrop occlusions is identified by comparing two successive images then sorting analysis using displacement formulae or by identifying them typically based on photometric or geometric properties of raindrop. The computation time and the accuracy for these approaches are trade off factors. In this paper, we propose an algorithm to detect the raindrop, where detection is performed using thresholding and feature transform only on single frame. The approach reduces the computation time and memory resource, executing only on current frame. Once the raindrop occlusion is affirmed, an interrupt is sent to the concurrent algorithm about the occlusions and abort the same. To retrieve the region from occlusion we follow one of the generic method employing Gauss filter.

关键词： ADAS computer vision raindrop detection thresholding feature transform

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Parallelizing band selection for hyperspectral imagery with many-threads 2

Parallelizing band selection for hyperspectral imagery with ...

引用

2nd international conference on image, vision and Computing, ICIVC 2017

作者： Gan, Xinbiao Liu, Jie School of Computer National University of Defense Technology Changsha China Sate Key Laboratory of Space Weather Chinese Academy of Sciences Beijing China Key Laboratory of Spectral Imaging Technology Chinese Academy of Sciences Xi'an China

ISBN: (纸本)9781509062379

It is time-consuming and expensive for band selection of hyperspectral imagery. In practice, band selection for hyperspectral imagery is a computing-intensive application, in which bands with less information are removed and the maximal information band should be preserved by quantifying information amount based on K-L divergence. Fortunately, it is suitable to parallelize band selection for hyperspectral imagery using accelerator with many-threads. Experimental results validate that band selection with China Accelerator would be much better than CPU and 1.25 X speedups than that of matched GPU. © 2017 IEEE.

关键词： Remote sensing

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Automatic Extraction Device Nameplate Area from Digital image

Automatic Extraction Device Nameplate Area from Digital Imag...

引用

2018 2nd international conference on Modeling, Simulation and Optimization Technologies and Applications(MSOTA 2018)

作者： Lin LI Xiao-bo LIU Yan-di LI Wuhan NARI Limited Liability Company of State Grid Power Research Institute Department of Computer Science and Technology China University of Geosciences

Since that nameplate recognition plays an important role in intelligent manufacturing,we explored an image processing solution based on the digital image of the metal nameplate of power equipment. At first, the gray image and threshold segmentation are used to realize the image preprocessing. After this, the application of the three edge detection operators of the scharr operator, the sobel operator and the canny operator in the actual image is compared to realize the image edge detection process. Based on the morphological method, the noise elimination effects of three different structural elements and convolution kernel are analyzed afterwards. The method of identifying the nameplate area in steps is designed. Finally, through the contour detection and perspective projection, the image processing results are improved, and the extraction process of the complete digital image nameplate area in complex environment is realized.

关键词： Machine vision Convolution kernel Morphology filter Object recognition

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An experimental evaluation of different face recognition algorithms using closed circuit television images 2

An experimental evaluation of different face recognition alg...

引用

2nd IEEE international conference on Signal and image processing, ICSIP 2017

作者： Fahad, Shahzada Ur Rahman, Sami Khan, Imran Haq, Sanaul Department of Computer Science and Information Technology University of Malakand Khyber Pakhtunkhwa Pakistan

ISBN: (纸本)9781538609682

Bio-metric based recognition is rapidly replacing the non-biometric based recognition systems. Face recognition is one of the most important bio-metric based recognition technique. Different algorithms exist for face recognition that works well on high resolution digital images. The aim of this work is to check whether these existing face recognition algorithms work on low quality Closed Circuit Television images? We have considered three such algorithms. These algorithms are Artificial Neural Network, Principal Component Analysis and Single Value Decomposition. We have experimentally evaluated these for Closed Circuit Television images. Our experiments show that using the CCTV images the accuracy rate of ANN for face recognition is 85%, for PCA the accuracy rate is 75% and for SVD the accuracy rate is 65%. The experiments also show that the accuracy of all the three algorithms reduces when the number of input faces increases. © 2017 IEEE.

关键词： Face recognition

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Hybrid broadcasting scheme combining FB+ and DeRe schemes for heterogeneous receivers 2

Hybrid broadcasting scheme combining FB+ and DeRe schemes fo...

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2nd international conference on Multimedia and image processing, ICMIP 2017

作者： Xiao, Linghao Wang, Xingjun Zhong, Zhanwei Department of Electronic Engineering Graduate School at Shenzhen Tsinghua University Shenzhen China Department of Electrical and Computer Engineering Duke University Durham United States

ISBN: (纸本)9781509059546

The most efficient way to solve large scale videostreaming problem is periodic broadcasting for popular *** studies mainly focus on reducing client's waiting timeand buffer demand. Later, researchers focused on the problemof heterogeneity among clients' reception *** can be categorized in two types: ReceptionBandwidth Adaptable (RBA) approach and ReceptionBandwidth Limited (RBL) approach. Both approaches havetheir pros and cons and a recently proposed DeRe scheme hassuccessfully kept the advantages of both approaches *** this paper, we propose a Hybrid Broadcasting (HyB)scheme which combines FB+ structure and DeRe schemetogether. The proposed scheme not only maintains goodperformance as DeRe scheme in service latency and bufferrequirement, but also overcome the drawbacks of DeRescheme such as large number of video segments to manage andfrequent channel hopping in client's reception path. HyBscheme is also buffer controllable by adjusting the bufferdemand of its DeRe scheme part. © 2017 IEEE.

关键词： Video on demand

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IR sensing embedded system development for prototype mobile platform for autonomous convoy 2

IR sensing embedded system development for prototype mobile ...

引用

2nd IEEE international conference on Signal and image processing, ICSIP 2017

作者： Bryan Riley, H. Celenk, Mehmet School of Electrical Engineering and Computer Science Stocker Center Ohio University AthensOH45701 United States

ISBN: (纸本)9781538609682

Sensing techniques using varied configurations of infrared (IR) devices are rapidly becoming a proven approach for autonomous vehicles. In this paper, we present an investigation and corresponding results of embedding these sensors in a prototype robotic model and examine its performance. The results support IR sensing as a viable alternative to a RADAR based system for object detection and travel in a forward path direction. Proportional Integral (PI) control is implemented due to its simplicity and effectiveness in Python programming language on the Raspberry Pi microcomputer. In this research, we model the operational characteristics of IR sensors in accordance with the physical principal that the measured distance is inversely proportional to the IR sensor voltage output. This provides a device independent robust sensing methodology as demonstrated in the experimental section of the undertaken research. As a result, the proposed approach is expected to enable major manufacturers and corporations to have fully autonomous passenger cars and trucks on roads in the USA by 2021. [1] © 2017 IEEE.

关键词： Autonomous vehicles

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Characteristic extraction, classification and identification algorithm based on two kinds of eaglewood micrographs 2

Characteristic extraction, classification and identification...

引用

2nd international conference on image, vision and Computing, ICIVC 2017

作者： Haifeng, Wang Kun, Zhang Li, Zhuang College of Ocean Information Engineering/Sanya Key Laboratory of Computer Vision Hainan Tropical Ocean University China College of Information Science and Technology Hainan University Haikou China College of Ocean Information Engineering/Division of Development and Planning Hainan Tropical Ocean University Sanya China

ISBN: (纸本)9781509062379

In order to classify the eaglewood, the work proposed a method of wood fiber segmentation and characteristic extraction based on the eaglewood micrographs. The active contour model was used to extract the contours of the eaglewood micrographs. After screening of wood fiber, the geometric features and shape factors were extracted to form characteristic vectors. After that, SVM was used to achieve the classification of the two kinds of eaglewood micrographs. Results show that the extracted characteristics can be used to express eaglewood fiber. With good classification performance, classification algorithm is easy to achieve. © 2017 IEEE.

关键词： Extraction

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ROBOIC RECOGNITION FOR UNSTRUCTERED 2-D PARTS TO PICK And PLACE OBJECTS 2

ROBOIC RECOGNITION FOR UNSTRUCTERED 2-D PARTS TO PICK AND PL...

引用

2nd IEEE international conference on Recent Trends in Electronics, Information and Communication Technology (RTEICT)

作者： Nalini, K. M. Gondkar, Raju R. VTU RRC Dept CSE Belagavi Karnataka India Nagarjuna Coll Engn Technol Dept MBA Bangalore Karnataka India

ISBN: (纸本)9781509037049

Robot grasping of unstructured objects to pick and place in a home environment is a problem in autonomous assembly. Current investigation focus on technology related with machine vision for image manipulation. Desired grasping location is found out from 2-D vision by the bounding rectangle and bounding rectangle diagonal to calculate total number of pixel on parts. Various steps are adopted especially tools and built-in functions of LabVIEW for image acquisition, manipulations, and processing. These tools and functions helped us to create efficient algorithm for object recognition, grasping of sensitive and hard objects without fail. The system contains routine functions for database creation, learning, training, searching, monitoring, and controlling of autonomous mobile robot. Communication between hardware to software and viz versa are configured by VISA resource through COM port. Experiments analysis is done for evaluation of robot in real time.

关键词： Grasping LabVIEW machine vision object recognition

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Effect Of image Colourspace On Performance Of Convolution Neural Networks 2

Effect Of Image Colourspace On Performance Of Convolution Ne...

引用

2nd IEEE international conference on Recent Trends in Electronics, Information and Communication Technology (RTEICT)

作者： Reddy, K. Sumanth Singh, Upasna Uttam, Prakash K. DIAT DU Pune Dept Mech Engn Pune Maharashtra India DIAT DU Pune Dept Comp Engn Pune Maharashtra India R&D Engn DRDO Pune Electro Mech Syst Grp Pune Maharashtra India

ISBN: (纸本)9781509037049

Recently the term Deep Learning has been creating a lot of interest in the fields of Artificial Intelligence, computer vision and Natural Language processing. And especially the Convolution Neural Networks (CNN) are giving state of art results in image recognition, scene understanding, object detection and image description etc. Generally in CNN the processing of images is done in RGB colourspace even though we have many other colourspaces available. In this paper we try to understand the effect of image colourspace on the performance of CNN models in recognizing the objects present in the image. We evaluate this on CIFAR10 dataset, by converting all the original RGB images into four other colourspaces like HLS, HSV, LUV, YUV etc. To compare results we have trained AlexNet with fixed set of parameters on all five colourspaces, including RGB. We have observed that LUV colourspace is the best alternative to RGB colourspace to use with CNN models with almost equal performance on the test set of CIFAR10 dataset. While YUV colourspace is the worst to use with CNN models.

关键词： Convolution Neural Networks Colourspace CIFAR10 Object Recognition

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Leaf Disease Detection on Cucumber Leaves Using Multiclass Support Vector Machine 2

Leaf Disease Detection on Cucumber Leaves Using Multiclass S...

引用

2nd IEEE international conference on Wireless Communications, Signal processing and Networking (WiSPNET)

作者： Krithika, P. Veni, S. Amrita Univ Amrita Vishwa Vidyapeetham Amrita Sch Engn Dept Elect & Commun Engn Coimbatore 641112 Tamil Nadu India

ISBN: (纸本)9781509044429

In India, smart organic farming is gaining importance. There may be problems due to environment, temperature, humidity or nutrient deficiency in this farming. If we have a monitoring system for this farming it is possible to produce healthy plant. The aim is to address this issue using computer aided image processing technique. Main solution is to create an automation system which can detect the disease present in the leaf of the plant. In this paper, a first level attempt is made to detect diseases present in the leaf of salad cucumber. The most common diseases which are present in salad cucumber are Alternaria leaf blight, Bacterial wilt, Cucumber green mottle mosaic, Leaf Miner, Leaf spot, Cucumber Mosaic Virus (CMV) disease and so on. K-means clustering, an unsupervised algorithm along with Support Vector Machine(SVM) is used in this work to address this problem.

关键词： k-means clustering Multiclass SVM image processing

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