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Lossless Compression of Maps, Charts, and Graphs via Color Separation

Lossless Compression of Maps, Charts, and Graphs via Color S...

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Data Compression Conference (DCC)

作者： Saif alZahir Arber Borici Graphics and Image Processing Laboratory Computer Science University of Northern British Columbia BC Canada

ISBN: (纸本)9781424464258

Summary form only given. In this research, we present a fast and efficient lossless compression scheme for discrete-color digital map images, charts, and graphs stored in the raster image format. The proposed scheme determines the number of different colors in the given image and creates a separate bi-level data layer for each color. Then, the bi-level layers are individually compressed using the proposed algorithm. This scheme comprises two components: (i) a codebook; and (ii) our row-column reduction coding algorithm, RCRC. The codebook is a fixed-to-variable Huffman dictionary that is based on symbol entropy. The second component of our scheme is a new algorithm, the RCRC, designed to deal with those blocks that are not found in the codebook. Our experimental results show that our lossless compression scheme achieved an average compression equal to 0.035 bpp for map images and 0.03 bpp for charts and graphs. These results are better than most reported results in the literature. Moreover, our scheme is simple and fast.

关键词： image coding Frequency Data compression Color computer graphics image processing computer science Partitioning algorithms Dictionaries Entropy

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Virtual housing design experience platform

Virtual housing design experience platform

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International Conference on Multimedia Technology

作者： Dai, Dameng Ding, Jianhao Wang, Yigang College of Physics and Electronic Information and Engineering Wenzhou University Wenzhou China Institute of Computer Graphics and Image Processing Hangzhou Dianzi University Hangzhou China State Key Laboratory of CAD and CG Zhejiang University Hangzhou China

ISBN: (纸本)9781424478743

Traditional display fashions of housing design mainly depend on static pictures, which are short of the intuition of house space and do not support interaction during design periods. This paper proposes a virtual housing design experience platform consist of a cheap hardware VR environment and housing design software system we developed. With this design platform, a fast generating virtual house permits intuitive and precise interaction in the VR environment. Customers can modify the design of their home and have a pseudo experience of their virtual house in real time. The system will give advice on layout design, providing a complete and precise house space representation and the support for real time visualization. ©2010 IEEE.

关键词： Virtual reality

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A Low Complexity Wavelet-Packets Based image Signature for Indexing and Retrieval

A Low Complexity Wavelet-Packets Based Image Signature for I...

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Canadian Conference on Electrical and computer Engineering (CCECE)

作者： Saif Zahir Computer Science Department UNBC Image Processing Multimedia and Graphics Laboratory Prince George BC Canada

image signature is a signal that is significantly shorter and simpler than the image signal and can be used to efficiently identify the original image. Generating an image signature that accurately represents an image can only be done by means of extracting specific features of the image and express it in an efficient way. In this paper, a new wavelet-packets-based (WP) image signature that can be used for image indexing and fast retrieval is proposed. This signature is generated via encoding the position of specific points of the signal that represents some statistics of the wavelet packets coefficients in the various frequency bands. computer simulation results using nearly 7500 image signatures show that the targeted image signature was identified with a very high accuracy in a very short period of time. Also, it showed that the proposed signature is robust against geometric transformation

关键词： Wavelet packets Indexing image retrieval Signal processing image generation Feature extraction Signal generators Encoding Statistics Frequency

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Parallel conflict-free optimal access to complete extended Q-ary trees 4th

Parallel conflict-free optimal access to complete extended Q...

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4th International Workshop on Parallel processing by Cellular Automata and Arrays, Parcella 1988

作者： Creutzburg, Reiner Academy of Sciences of the G.D.R Central Institute of Cybernetics and Information Processes International Basic Laboratory for Image Processing and Computer Graphics Kurstrasse 33 P.O.Box 1298 BerlinDDR-1086 Germany

ISBN: (纸本)9783540506478

In this paper we investigate the parallel conflict-free access to complete extended q-ary subtrees of complete q-ary trees. Thereby the memory module assignment function S is supposed to be recursively linear and nonlinear. Known results for extended binary subtree access are generalized to the case of extended q-ary subtrees. Furthermore optimal solutions for isotropic nonlinear extended q-ary subtree access are given. © by Akademie-Verlag Berlin 1989.

关键词： Forestry

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Optimal surface normal from affine transformation 10

Optimal surface normal from affine transformation

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10th International Conference on computer Vision Theory and Applications, VISAPP 2015

作者： Daniel, Barath Molnar, Jozsef Hajder, Levente Geometric Modelling and Computer Vision Laboratory MTA SZTAKI Kende utca 13-17 BudapestH-1111 Hungary Department of Image Processing and Computer Graphics Institute of Informatics University of Szeged Árpád tér 2 SzegedH-6720 Hungary

ISBN: (纸本)9789897580918

This paper deals with surface normal estimation from calibrated stereo images. We show here how the affine transformation between two projections defines the surface normal of a 3D planar patch. We give a formula that describes the relationship of surface normals, camera projections, and affine transformations. This formula is general since it works for every kind of cameras. We propose novel methods for estimating the normal of a surface patch if the affine transformation is known between two perspective images. We show here that the normal vector can be optimally estimated if the projective depth of the patch is known. Other non-optimal methods are also introduced for the problem. The proposed methods are tested both on synthesized data and images of real-world 3D objects.

关键词： Cameras

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Research on Chinese Summary Generation Based on Pointer Key Information 5

Research on Chinese Summary Generation Based on Pointer Key ...

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5th International Conference on computer Information Science and Application Technology, CISAT 2022

作者： Huang, Wenming Bu, Xianghui Xiao, Yannan Wen, Yayuan Deng, Zhenrong School of Computer and Information Security Guilin University of Electronic Technology Guangxi Guilin China Guangxi Key Laboratory of Image and Graphics Intelligent Processing Guangxi Guilin China College of Electronic Engineering Guangxi Normal University Guangxi Guilin China

ISBN: (纸本)9781510660076

Sequence-to-sequence models provide a feasible new approach for generative text summarization, but these models are not able to accurately reproduce factual details and subject information. To address the problem of unconstrained and uncontrollable content generation of generative text summarization models, this paper proposes a generative summarization method KGIT that uses Transformer as a skeleton and incorporates both BERT pre-training model and keyword information. The model uses a comprehensive keyword extraction algorithm, uses two results extracted by LSTM and TextRank as vocabularies respectively, and uses pointers keywords are selected and the extracted keywords are used as the guiding information to generate the summary based on the guiding information. KGIT model can associate the source text and keywords to avoid generating a summary of irrelevant topics. The ROUGE value is used as the evaluation criterion for text summaries, and the summaries generated by the KGIT model can contain more key information and are more accurate and readable when compared with the mainstream summary generation models on the NLPCC2017 Chinese news summary dataset. © 2022 SPIE.

关键词： Natural language processing systems

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Insulator Defect Detection Algorithm Based on Improved YOLOv5s 5

Insulator Defect Detection Algorithm Based on Improved YOLOv...

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5th International Conference on computer Information Science and Application Technology, CISAT 2022

作者： Huang, Wenming Li, Tingting Xiao, Yannan Wen, Yayuan Deng, Zhenrong School of Computer and Information Security Guilin University of Electronic Technology Guangxi Guilin China Guangxi Key Laboratory of Image and Graphics Intelligent Processing Guangxi Guilin China College of Electronic Engineering Guangxi Normal University Guangxi Guilin China

ISBN: (纸本)9781510660076

As one of the extremely important components on the transmission tower, the insulator has two functions of electrical insulation and wire fixing, which directly affects the operation of the power system. Defects in insulators can impair the service life of transmission lines. UAV aerial photography of electric power towers has problems such as small number of defective insulator samples, small area, large aspect ratio of insulator strings, and variable inclination angle, coupled with the influence of environmental factors such as light, interference, distance, etc., which lead to low detection accuracy of insulator defects. Aiming at the above problems, an improved YOLOv5 insulator defect detection algorithm is proposed. First, screen the aerial images and use data augmentation to obtain a sufficient number of defective insulator images to enrich the dataset and avoid model overfitting. Secondly, the convolutional attention module CBAM is introduced to improve the expression ability of defect insulator features and strengthen the network's ability to identify targets. Finally, the Leaky ReLU activation function of the hidden layer of the original YOLOv5 algorithm is replaced by the Mish function to improve the generalization ability of the network. The experimental results show that compared with the original YOLOv5 algorithm, the average precision mAP (IOU=0.5) of the improved algorithm is increased by 7.8%, which effectively improves the problems of false detection and missed detection in the original algorithm. Compared with other mainstream object detection algorithms, the algorithm proposed in this paper has better detection effect on insulator defects. © 2022 SPIE.

关键词： Defects

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Multi-Contextual and Multi-Aspect Analysis for Road Surface Type Classification Through Inertial Sensors and Deep Learning

Multi-Contextual and Multi-Aspect Analysis for Road Surface ...

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Brazilian Symposium on Computing System Engineering (SBESC)

作者： Jeferson Menegazzo Aldo von Wangenheim Graduate Program in Computer Science (PPGCC) Image Processing and Computer Graphics Lab (LAPIX) Brazilian National Institute for Digital Convergence (INCoD) Federal University of Santa Catarina (UFSC) Florianópolis Brazil

ISBN: (数字)9781728182865

ISBN: (纸本)9781728182872

The demand for a variety of situational data from the traffic environment and its participants has intensified with the development of applications in Intelligent Transport Systems (ITS). Among these data, the road surface type classification is one of the most important and can be used in the entire ITS domain. For its widespread application, it is necessary to employ a robust technology for the generation of raw data and to develop of a reliable and stable model to process these data in order to produce the classification. The developed model must operate correctly in different vehicles, under different driving styles and in different environments in which a vehicle can travel. In this work we employ inertial sensors, represented by accelerometers and gyroscopes, which are a safe, non-polluting, and low-cost alternative, ideal for large-scale use. We collect nine datasets with contextual variations, including three different vehicles, with three different drivers, in three different environments, in which there are three different road surface types, in addition to variations in the conservation state and presence of anomalies and obstacles such as potholes and speed bumps. After data collection, these data were used in experiments to evaluate various aspects, such as the influence of the vehicle data collection point, the analysis domain, the model input features, and the data window. Afterwards we evaluated the learning and generalization capacity of the models for unknown contexts. In a third step, the data were used in three Deep Neural Network (DNN) models: LSTM-based, GRU-based, and CNN-based. Through a multi-aspect and multi-contextual analysis, we considered the CNN-based model as the best one, which obtained an average accuracy between the data collection placements of 94.27% for learning and 92.70% for validation, classifying the road surface between asphalt, cobblestone or dirt road segments.

关键词： Roads Sensors Data models Vehicles Sensor systems Deep learning Data collection

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Chinese Text Summarization Generation Based on Transformer and Temporal Convolutional Network 2

Chinese Text Summarization Generation Based on Transformer a...

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2nd International Conference on Electronic Information Technology, EIT 2023

作者： Huang, Wenming Zhou, Yaowei Xiao, Yannan Wen, Yayuan Deng, Zhenrong School of Computer and Information Security Guilin University of Electronic Technology Guangxi Guilin China Guangxi Key Laboratory of Image and Graphics Intelligent Processing Guangxi Guilin China College of Electronic Engineering Guangxi Normal University Guangxi Guilin China

ISBN: (数字)9781510666627

ISBN: (纸本)9781510666610

The recurrent neural network model based on attention mechanism has achieved good results in the text summarization generation task, but such models have problems such as insufficient parallelism and exposure bias. In order to solve the above problems, this paper proposes a two-stage Chinese text summarization generation method based on Transformer and temporal convolutional network. The first stage uses a summary generation model that fuses Transformer and a temporal convolutional network, and generates multiple candidate summaries through beam search at the decoding end. In the second stage, contrastive learning is introduced, and the candidate summaries are sorted and scored using the Roberta model to select the final summary. Through experiments on the Chinese short text summarization dataset LCSTS, ROUGE was used as the evaluation method to verify the effectiveness of the proposed method on Chinese text summarization. © 2023 SPIE.

关键词： Convolution

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On the optimization of tolerance synthesis with an ontology-based approach

On the optimization of tolerance synthesis with an ontology-...

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Chinese Automation Congress (CAC)

作者： Hongcheng Lu Meifa Huang Yanru Zhong Congwen Zheng Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology Guilin PR China

ISBN: (纸本)9781467371902

In general, mechanical designers have to manually select assembly tolerance types and values in product design. To reduce the uncertainty in manufacturing process, solve the problem of effectively sharing and smoothly exchange tolerance information among heterogeneous CAD system. On the optimization of tolerance synthesis with an ontology-based approach is proposed, automatically generated the tolerance type, variations of tolerance, cost function and tolerance value. Firstly, ontology contains abundant semantic knowledge and semantic structure. Secondly, the Web Ontology Language (OWL) is used to define the concepts of tolerance synthesis, and Semantic Web Rule Language (SWRL) is used to define the constraint conditions and distribute experience. Thirdly, based on the genetic algorithm, a tolerance values optimization model is established with manufacturing cost functions and assembly stack-up constraint. Finally, the effectiveness of the proposed approach is illustrated by using a practical example of the gear case.

关键词： Assembly Cost function Feature extraction Ontologies Solid modeling

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