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检索条件"任意字段=1st International Conference on Digital Image Processing and Pattern Recognition, DPPR 2011"

共 114 条记录，以下是1-10 订阅

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2nd international Workshop on Recent Advances in digital Security: Biometrics and Forensics, BioFor 2019, 1st international Workshop on pattern recognition for Cultural Heritage, PatReCH 2019, 1st international Workshop eHealth in the Big Data and Deep Learning Era, e-BADLE 2019, international Workshop on Deep Understanding Shopper Behaviors and Interactions in Intelligent Retail Environments, DEEPRETAIL 2019 and Industrial session held at the 20th international conference on image Analysis and processing, ICIAP 2019

2nd International Workshop on Recent Advances in Digital Sec...

引用

2nd international Workshop on Recent Advances in digital Security: Biometrics and Forensics, BioFor 2019, 1st international Workshop on pattern recognition for Cultural Heritage, PatReCH 2019, 1st international Workshop eHealth in the Big Data and Deep Learning Era, e-BADLE 2019, international Workshop on Deep Understanding Shopper Behaviors and Interactions in Intelligent Retail Environments, DEEPRETAIL 2019 and Industrial session held at the 20th international conference on image Analysis and processing, ICIAP 2019

ISBN: (纸本)9783030307530

The proceedings contain 39 papers. The special focus in this conference is on Recent Advances in digital Security. The topics include: Modern vs Diplomatic Transcripts for Historical Handwritten Text recognition;improving Ancient Cham Glyph recognition from Cham Inscription images Using Data Augmentation and Transfer Learning;Oracle Bone Inscription Detector Based on SSD;shot Boundary Detection for Automatic Video Analysis of Historical Films;the Epistle to Cangrande Through the Lens of Computational Authorship Verification;a Cockpit of Measures for image Quality Assessment in digital Film Restoration;augmented Reality for the Valorization and Communication of Ruined Architecture;classification of Arabic Poems: from the 5th to the 15th Century;a Page-Based Reject Option for Writer Identification in Medieval Books;on the Cross-Finger Similarity of Vein patterns;minimizing Training Data for Reliable Writer Identification in Medieval Manuscripts;fusion of Visual and Anamnestic Data for the Classification of Skin Lesions with Deep Learning;slide Screening of Metastases in Lymph Nodes via Conditional, Fully Convolutional Segmentation;A Learning Approach for Informative-Frame Selection in US Rheumatology images;a Serious Game to Support Decision Making in Medical Education;nerve Contour Tracking for Ultrasound-Guided Regional Anesthesia;Skin Lesions Classification: A Radiomics Approach with Deep CNN;semantic 3D Object Maps for Everyday Robotic Retail Inspection;collecting Retail Data Using a Deep Learning Identification Experience;a Large Scale Trajectory Dataset for Shopper Behaviour Understanding;Improving Multi-scale Face recognition Using VGGFace2;An IOT Edge-Fog-Cloud Architecture for Vision Based Pallet Integrity;the Vending Shopper Science Lab: Deep Learning for Consumer Research.

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Intelligent image recognition and Classification Technology in digital Media 1st

Intelligent Image Recognition and Classification Technology ...

引用

1st international conference on pattern Analysis and Machine Intelligence, ICPAMI 2024

作者： Liang, Huan Guangzhou International Economics College Guangzhou510540 China

ISBN: (纸本)9789819633487

With the increasing popularity of digital media along with the fact that massive image data has already gained popularity, the automatic image recognition and classification have become a very critical and urgent problem, this study investigates and tests intelligent image recognition and classification techniques for digital media based on major methods such as CNN, SVM and RNN. Different algorithms and models are applied to training and test image data to evaluate the performance of various methods in terms of accuracy and processing time. The experimental results shows that the CNN method can achieve high accuracy in image classification task and the multi-layer convolution and pooling operations can effectively extract image features. The SVM method is better than the CNN in terms of processing time but have slightly lower accuracy. The RNN method is ranked between the CNN and SVM in terms of accuracy and processing time. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： image representation

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Advances in digital image processing and Information Technology - First international conference on digital image processing and pattern recognition, dppr 2011, Proceedings

Advances in Digital Image Processing and Information Technol...

引用

1st international conference on digital image processing and pattern recognition, dppr 2011

ISBN: (纸本)9783642240546

The proceedings contain 47 papers. The topics discussed include: fuzzy soft thresholding based hybrid denoising model;content-based image retrieval using a quick SVM-binary decision tree - QSVMBDT;a hybrid approach to estimate true density function for gene expression data;unsupervised medical image classification based on skew Gaussian mixture model and hierarchical clustering algorithm;writer based handwritten document image retrieval using contourlet transform;a study on block matching algorithms and gradient based method for motion estimation in video compression;digital video watermarking using motion detection and singular value decomposition;stegno-image generator (SIG) - building steganography image database;prototype based performance prediction of web services;the goal of securing mobile ad-hoc network and solutions;and elements of cloud computing: a perspective on service oriented enterprises (SOEs).

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Extraction of Urban Road Network by Performing Edge - Aided Classification in Remote Sensing

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1st international conference on digital image processing and pattern recognition (dppr 2011)

作者： Rajalakshmi, K. Dhinaharan, A. L. Murugan, D. Singaravelan, S. Manonmaniam Sundaranar Univ Dept Comp & Informat Technol Tirunelveli India Wireless sensor Networks Div Melbourne Vic Australia Manonmaniam Sundaranar Univ Dept Comp Sci & Engn Tirunelveli India PSR Engn Coll Dept Comp Sci & Engn Sivakasi India

ISBN: (纸本)9783642240546;9783642240553

A new approach for object extraction from high-resolution satellite images is presented in this paper. The new approach integrates image fusion, multi-spectral classification, feature extraction and feature segmentation into the object to improve accuracies. This paper mainly concentrates on road extraction from quick bird MS and Pan images using the proposed approach. Experiments of road extraction with Quick Bind MS and Pan images demonstrate that the proposed approach is effective.

关键词： digital Urban Object Edge - Aided Extraction

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Satellite image processing Using Discrete Cosine Transform and Singular Value Decomposition

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1st international conference on digital image processing and pattern recognition (dppr 2011)

作者： Ashish, B. K. Kumar, A. Padhy, P. K. PDPM Indian Inst Informat Technol Design & Mfg Jabalpur 482005 MP India

ISBN: (纸本)9783642240546;9783642240553

In this paper, a novel contrast enhancement technique for contrast enhancement of a low-contrast satellite image has been proposed based on the singular value decomposition (SVD) and discrete cosine transform (DCT). The singular value matrix represents the intensity information of the given image and any change on the singular values change the intensity of the input image. The proposed technique converts the image into the SVD-DCT domain and after normalizing the singular value matrix;the enhanced image is reconstructed by using inverse DCT. The visual and quantitative results suggest that the proposed SVD-DCT method clearly shows the increased efficiency and flexibility of the proposed method over the exiting methods such as the histogram equalization, gamma correction and SVD-DWT based techniques.

关键词： Singular Value Decomposition (SVD) discrete cosine transforms (DCT) image equalization and satellite image contrast enhancement

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digital Video Watermarking Using Motion Detection and Singular Value Decomposition

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1st international conference on digital image processing and pattern recognition (dppr 2011)

作者： Sinha, Sanjana Pramanick, Swarnali Jagatramka, Ankul Bardhan, Prajnat Kole, Dipak K. Chakraborty, Aruna St Thomas Coll Engn & Technol Dept Comp Sci Engn Kolkata 700023 India

ISBN: (纸本)9783642240546;9783642240553

Various digital watermarking techniques have been proposed in recent years for the purpose of protection of intellectual property rights of the creators of multimedia data, such as digital video. In order to achieve copyright protection of digital video we have adopted an imperceptible video watermarking approach based on Motion Detection and Singular Value Decomposition. Motion detection using temporal difference is used to identify the motion regions within a video frame where a watermark can be effectively embedded to ensure imperceptibility of the watermark. The unique properties of the singular values of an image, in this case the individual motion regions within the video frames, are utilized to enhance the robustness of watermarking and make it non-invertible. The resultant watermarked video is then tested for its robustness against attacks for watermark degradation and removal.

关键词： digital watermarking copyright protection motion detection singular value decomposition

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A Denoising Approach for Salt and Pepper Noise Corrupted image at Higher Noise Density

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1st international conference on digital image processing and pattern recognition (dppr 2011)

作者： Dey, Debika Laha, Samanwita Chowdhury, Shalini Sarker, Subhojit Siliguri Inst Technol Dept Elect & Commun Engn Darjeeling India

ISBN: (纸本)9783642240546;9783642240553

image restoration and noise reduction is an eminent problem in almost all image processing applications. Numerous image restoration methods have been developed, each of which has its own advantages and limitation. This paper proposes a novel approach for removal of salt and pepper noise using a two stage process, in which the noisy image is first subjected to an adaptive median filter and then its output is further denoised by applying it to a new patch based non- local recovery paradigm. The Non-Local means filter uses the redundancy of information in the image under study to remove the noise. The statistical results of simulations are done using MATLAB and the obtained denoised images are quantified using various performance metrics.

关键词： Adaptive median Filter Non-Local means filter Salt and pepper noise image restoration

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Design of Optimized Neuro-Wavelet Based Hybrid Model for image Compression

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1st international conference on digital image processing and pattern recognition (dppr 2011)

作者： Gambhir, Deepak Rajpal, Navin Singh, Vipula Amity Sch Engn & Technol ECE New Delhi India Guru Gobind Singh Inderprastha Univ USIT New Delhi India RNS Inst Technol ECE Bangalore Karnataka India

ISBN: (纸本)9783642240546;9783642240553

images are in its standard canonical form for a matrix have significant amount of redundant data. Thus image compression methods always under wide attention for efficient multimedia data transmission and storage. This paper concerned with the design of an optimized hybrid Neuro-Wavelet based model for image compression. In this design first the images are decomposed to various sub-band via wavelet transform and then they are fed to different supervised Neural Networks which are optimized with Linear Programming. The simulation results show the clear improvement over the existing methods objectively by PSNR and subjectively by visual appearance.

关键词： image Compression Back Propagation Neural Network Wavelet Transform Linear Programming

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Writer Based Handwritten Document image Retrieval Using Contour let Transform

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1st international conference on digital image processing and pattern recognition (dppr 2011)

作者： Shirdhonkar, M. S. Kokare, Manesh B. Coll Engn BLDEAs Bijapur India SGGS Inst Engn & Technol Nanded India

ISBN: (纸本)9783642240546;9783642240553

Many techniques have been reported for handwritten based document image retrieval. This paper proposes a novel method by using Contourlet Transform (CT) for feature extraction of document images which achieves high retrieval rate. The handwriting of different people is often visually distinctive;we take a global approach based on texture analysis, where each writer's handwriting is regarded as a different texture. The Canberra distance is used as similarity measure in proposed system. A retrieval result with proposed method is very promising with precision and recall as compared to the existing system.

关键词： Document image analysis and retrieval CT document similarity measurement handwritten documents handwriting classification and retrieval writer identification

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Semantic Learning in Interactive image Retrieval

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1st international conference on digital image processing and pattern recognition (dppr 2011)

作者： Patil, Pushpa B. Kokare, Manesh BLDEAs VPDr PG Halakatti CET Dept Comp Sci & Engg Bijapur India SGGS Inst Engn & Technol Dept Elect & Telecommun Nanded India

ISBN: (纸本)9783642240546;9783642240553

This paper presents content-based image retrieval frameworks with relevance feedback based on AdaBoost learning method. As we know relevance feedback (RF) is online process. so we have optimized the learning process by considering the most positive image selection on each feedback iteration. To learn the system we have used AdaBoost. The main significances of our system are to address the small training sample and to reduce retrieval time. Experiments are conducted on 1856 texture images to demonstrate the effectiveness of the proposed framework. These experiments employed large image databases and combined RCWFs and DT-CWT texture descriptors to represent content of the images.

关键词： Content-Based image Retrieval (CBIR) Relevance Feedback (RF) Rotated Complex Wavelet Filters (RCWFs) Dual Tree Complex Wavelet (DT-CWT) and image retrieval

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