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检索条件"任意字段=Conference on Storage and Retrieval for Image and Video Databases III"

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video searching and retrieval using scene classification in multimedia databases 2

Video searching and retrieval using scene classification in ...

引用

2nd International conference for Emerging Technology, INCET 2021

作者： Haloi, Pranabjyoti Bhuyan, M.K. Indian Institute of Technology Guwahati Department of Electronics and Electrical Engineering Guwahati India

ISBN: (纸本)9781728170299

image and video indexing techniques play a key role in content-based searching in multimedia databases. A novel efficient video similarity search approach for content-based video retrieval in a large storage device is proposed. A compressed domain feature is used to classify the scenes of a video sequence. The performance of the said feature in classifying the scenes is evaluated by considering different feature lengths. Subsequently, a novel searching algorithm is proposed based on entropy of the image. This method incorporates temporal information of the video during video retrieval. Additionally, the proposed system has the facility to query both by video and by image. The 92.3% accuracy of the proposed method exceeded that of the VA-file 81.0% and OVA-file 76.4% methods and the computational complexity was lower than the VA-file method. This demonstrates the efficiency and effectiveness of the proposed method. © 2021 IEEE.

关键词： Classification (of information)

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Vehicle Number Plate Recognition and Information Access System

Vehicle Number Plate Recognition and Information Access Syst...

引用

Sustainable Computing and Integrated Communication in Changing Landscape of AI (ICSCAI), International conference on

作者： Pradeep B. Mane Varsha Kiran Patil Mayur R. Paithankar Mallikarjun M. Kotgire Samveg S. Shah Dept. Electronics and Telecommunication AISSMS Institute of Information Technology Pune India

ISBN: (数字)9798350355338

ISBN: (纸本)9798350355345

Addressing the growing challenges posed by increasing vehicles and stringent traffic violations, many vehicle number plates go undetected while passing through toll booths and traffic lights. Thus it creates the need for a vehicle number plate recognition system. Existing systems employing ANPR algorithms utilize MATLAB and K-Nearest neighbour algorithms for image processing. Drawbacks include limitations in adapting to dynamic environments, Real time recognition, handling multiple vehicles, slow processing speeds, incapability of multiple object detection in single frame. The paper focuses on Automatic Number Plate Recognition (ANPR), employing specialized cameras and advanced image processing and using YOLOv8 for object detection and extracting license plate information from video feeds using EasyOCR. The noisy data generated during character recognition is filtered out using Regex based algorithm. The system integrates with centralized databases for real-time vehicle information access for users. The same database is used to automate e-challan updation, contributing to traffic management by swiftly issuing fines for rule violations. The proposed video-based processing system achieves number plate detection using YOLOv8 and storage of vehicle number plates in a centralized MongoDB database with an accuracy achieved of 96% in license plate detection and reduces noisy data using algorithm. It also enables real-time data retrieval through a user interface using Reactjs as frontend and is also connected to the MongoDB database for precise and user-friendly access in modern traffic systems.

关键词： image recognition databases Heuristic algorithms Object detection Filtering algorithms Information filters Real-time systems Character recognition Noise measurement License plate recognition

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Object retrieval in images using SIFT and R-CNN

Object Retrieval in Images using SIFT and R-CNN

引用

Innovative Trends in Information Technology (ICITIIT), International conference on

作者： I C Amitha N K Narayanan Kannur University Kerala India Indian Institute of Information Technology Kottayam Valavoor (P.O.) Kottayam Kerala

ISBN: (数字)9781728142104

ISBN: (纸本)9781728142111

image-based object retrieval has numerous applications in the field of machine vision to inquire from an appropriate image or video sequence for a given query object. The object retrieval task is conventionally carried out by a set of handcrafted algorithms, which provides image depictions in the fashion of visual characteristics. During the last decade, an extensive change has been practiced to describe visual content from handcrafted characteristics to the application of machine learning approaches and to the real layout of the image descriptors. The extensive movement is based on Convolutional Neural Networks (CNN) which is popularly known as Deep Learning. This proposed work deals with a combination of both conventional and machine learning approaches to retrieve an image object from a given dataset. This is done by a series of activities such as feature extraction and storage of training images, query image selection and feature extraction. Similarity matching between database and query image features. Final retrieval is based on the objectness score.

关键词： Convolutional neural networks Machine learning Feature extraction Task analysis Proposals Visualization databases

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Textual description based video annotation methods

Textual description based video annotation methods

引用

2018 International conference on Networking, Embedded and Wireless Systems, ICNEWS 2018

作者： Shama, P.S. Prakash, Pattan PDA College of Engineering Department of Computer Science and Engineering Kalaburagi585102 India

ISBN: (纸本)9781538679494

In the Present days, a large number of multimedia significant resources create the browsing, retrieval task. In this survey different types of methods are using, to foster the browsing of large video storage and provides sufficient access to contents. The video annotation initially cuts the detected video sequence, where the succeeding frames take out to show each shot or frames with a huge difference. The extraction of key frames that shows in every image is compressing the few images by using standard technologies like HOG, fuzzy clustering and Genetic algorithm regarding the textual depiction of the scene. video Annotation improves the sufficient searching and retrieving of the video components. They are inspired and are sometimes directly taken from image techniques. Thus, numerous varieties of images are easily applied to video annotation. © 2018 IEEE.

关键词： Genetic algorithms

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Web-based Multimedia Research and Indexation for Big Data databases 3

Web-based Multimedia Research and Indexation for Big Data Da...

引用

3rd International conference of Cloud Computing Technologies and Applications (CloudTech)

作者： Belarbi, Mohammed Amin Mahmoudi, Said Belalem, Ghalem Mahmoudi, Sidi Ahmed Univ Mons Fac Engn 20 Pl Parc Mons Belgium Ahmed Ben Bella Univ Oran1 Fac Exact & Appl Sci Oran Algeria

ISBN: (纸本)9781538611159

Indexing images represents a necessary tool for various domains related to computer vision such as video surveillance and movements analysis. Visual characteristics of image such as color, texture, shape are used to identify the content of these frames. The high increase of data (Big Data) makes us face a problem of curse of dimensionality. In this paper, we propose a cloud-based technique for images indexing images using PCA (Principal component analysis) and a binary tree. Our work consists of exploiting SIFT (Scale Invariant Feature Transform) and SURF (Speeded up Robust Features) descriptors as frames features, PCA as dimensionality reduction method of SIFT and SURF features and the binary tree representation of these images in order to accelerate the research phase and reduce the storage space. Our approach consists of developing a system based on three phases: indexing images with SIFT and SURF features, compression within the application of PCA and finally the image retrieval in the cloud.

关键词： Indexing images SIFT SURF PCA Cloud Big Data

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Efficient image retrieval Using image and Audio Features in video Stream

Efficient Image Retrieval Using Image and Audio Features in ...

引用

International conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS)

作者： In-Kyoung Shin Hyochang Ahn Yong-Hwan Lee Dept. of Applied Computer Engineering Dankook University Yongin-si Korea Dept. of Smart Mobile Far East Uinversity Chungcheongbuk-do Korea

ISBN: (纸本)9781509009855

Recently, information has changed to the development of the information communication network and multimedia technology. The multimedia technology is used as application techniques including the storage, playback, compression, and so on. Also it has changed rapidly and extensively over the world. Therefore numerous search schemes such as the video retrieval, speech retrieval are required. Current video retrieval methods have various problems as following redundancy of data and the inconsistency of a keyword, and infringement of copyright. In this paper, we propose implementation of novel scheme that carried out efficient retrievals for audio signal and image in video stream as rapidly changing generation of information communication.

关键词： Feature extraction Streaming media Motion pictures Speech Speech recognition databases Multimedia communication

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An efficient content-based video retrieval for large databases

An efficient content-based video retrieval for large databas...

引用

IEEE International conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE)

作者： Cedillo-Hernandez, Antonio Cedillo-Hernandez, Manuel Garcia-Ugalde, Francisco Nakano-Miyatake, Mariko Perez-Meana, Hector Univ Nacl Autonoma Mexico Fac Ingn Div Ingn Elect Mexico City 04510 DF Mexico Inst Politecn Nacl Escuela Super Ingn Mecan & Elect Mexico City DF Mexico

ISBN: (纸本)9781467383295

Multimedia data grows fast due to advances in information technologies, creating the demand for efficient video indexing and object retrieval techniques. Traditional methods consume significant computational resources such as storage space and processing time. In this paper we propose an efficient content-based video retrieval system that is based on three main stages. The first stage involves computing the DC-image of each I-frame, from which a summarization process to extract key-frames is performed. During the second stage, a segmentation processes is applied to each key-frame in order to isolate the region of interest within it. Local features are extracted from the resulting area and are stored as the descriptor of the frame. The retrieval stage is carried out by computing the Euclidean distance and determines if its content is related with the video database. Experimental results show that the proposed approach is promising in terms of efficiency and effectiveness.

关键词： Efficient CBVR system video indexing DC-frame SURF

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A fast wavelet packet and PCA based image indexing and authentication method 28

A fast wavelet packet and PCA based image indexing and authe...

引用

2015 28th IEEE Canadian conference on Electrical and Computer Engineering, CCECE 2015

作者： Alzahir, Saif Singh, D. Department of Computer Science UNBC BCV2N4Z9 Canada Computer Science Department UNBC Canada

ISBN: (纸本)9781479958276

The rapid growth in image databases is presenting new research challenges in wide range of areas that span image indexing, image retrieval, authentication, and recognition. This paper presents a new algorithm for image indexing and authentication. Although the combination of wavelet transform and principal components analysis has been used in some image processing areas but they have not been used for image indexing and authentication before. The proposed algorithm is based on the extraction of selected features of images using principal components analysis and wavelet packets. The proposed algorithm addresses three main concerns: (i) search accuracy;(ii) time efficiency;and (iii) storage requirements. We use wavelet packets to decompose the image to its fundamental subbands then we apply PCA method to extract the features of the images. The extracted features are used to create image signatures. We have tested our algorithm on the ORL Database of Faces (the AT&T laboratories Cambridge Database), PIE database, Caltech-UCSD Birds 200 and other miscellaneous images from different sources. We compared our results with two other methods [2] and [13] and found that our method retrieved the query image with 100% efficiency which significantly higher than that of method [13] and it is much faster than both methods. © 2015 IEEE.

关键词： Principal component analysis

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Design and Implementation of Distributed video retrieval System in Air Monitoring Warning System

Design and Implementation of Distributed Video Retrieval Sys...

引用

International conference on Measuring Technology and Mechatronics Automation, ICMTMA

作者： Chen Na Zhu Ya Ling College of Software Engineering Lanzhou Institute of Technology Lanzhou China

ISBN: (纸本)9781467371445

The video monitoring system plays a decisive role on the security of the sensitive areas, the video will be recording when the system monitors a warning behavior, accumulating over a long period, which will produce a large amount of video information, It is becoming crucial that how to retrieve these massive video information effectively and efficiently. The Content-based video retrieval technology has been the research hotspots in recent years. This paper, with the mature technology of video key frame extraction, combining with the SIFT feature extraction and matching, as well as LSH mapping, realizes the video retrieval. During the process of feature extraction and matching to the video key frame, we realize the distributed processing and storage, using MapReduce parallel mode and HBase distributed storage system, which is the application development of the Content-based video retrieval on the parallel analysis and scalable storage.

关键词： Monitoring Feature extraction Indexes Distributed databases Streaming media image retrieval Distributed processing

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An Efficient Content-Based video retrieval for Large databases

An Efficient Content-Based Video Retrieval for Large Databas...

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International conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE)

作者： Antonio Cedillo-Hernández Manuel Cedillo-Hernández Francisco García-Ugalde Mariko Nakano-Miyatake Héctor Pérez-Meana Facultad de Ingeniería División de Ingeniería Eléctrica Universidad Nacional Autónoma de México D.F. México Sección de Estudios de Posgrado e Investigación Instituto Politécnico Nacional D.F México

Multimedia data grows fast due to advances in information technologies, creating the demand for efficient video indexing and object retrieval techniques. Traditional methods consume significant computational resources such as storage space and processing time. In this paper we propose an efficient content-based video retrieval system that is based on three main stages. The first stage involves computing the DCimage of each I-frame, from which a summarization process to extract key-frames is performed. During the second stage, a segmentation processes is applied to each key-frame in order to isolate the region of interest within it. Local features are extracted from the resulting area and are stored as the descriptor of the frame. The retrieval stage is carried out by computing the Euclidean distance and determines if its content is related with the video database. Experimental results show that the proposed approach is promising in terms of efficiency and effectiveness.

关键词： Feature extraction video sequences image color analysis image segmentation Streaming media Indexing

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