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检索条件"任意字段=International Conference on Computer Vision and Image Processing, CVIP 2016"

共 1407 条记录，以下是311-320 订阅

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An efficient algorithm for medical image fusion using nonsubsampled shearlet transform 1

引用

2nd international conference on computer vision and image processing, cvip 2017

作者： Vishwakarma, Amit Bhuyan, M.K. Iwahori, Yuji Indian Institute of Technology Guwahati Guwahati781039 India Department of Computer Science Chubu University KasugaiAichi487-8501 Japan

ISBN: (数字)9789811078958

ISBN: (纸本)9789811078941

Multimodal medical image fusion techniques are utilized to fuse two images obtained from dissimilar sensors for obtaining additional information. These methods are used to fuse computed tomography (CT) images with magnetic resonance images (MRI), MR-T1 images with MR-T2 images, and MR images with single photon emission computed tomography (SPECT) images. In proposed method, nonsubsampled shearlet transform (NSST) is used for decomposition of source images to attain the low-frequency and high-frequency bands. The low-frequency bands are fused using weighted saliency-based fusion criteria, and high-frequency bands are fused with the help of phase stretch transform (PST) features. Applying inverse NSST operation, fused image is obtained. The results show the proposed method produces better results compared to state-of-the-art methods. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Magnetic resonance

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Deep Learning Based image Enhancement and Black Box Filter Parameter Estimation 1

引用

5th international conference on computer vision and image processing, cvip 2020

作者： Sharma, Mrigakshi Mittar, Rishabh Chakraborty, Prasenjit Samsung Research India Bangalore KA560037 India

ISBN: (数字)9789811610929

ISBN: (纸本)9789811610912

It is the age of social media and influencer culture and the importance of style and aesthetic has never been more apparent. Photo-retouching remains a critical and often, time consuming part of this process. To simplify the complex and skillful task of retouching, this paper proposes a Deep Learning based automatic photo retouching solution. It builds upon a GAN-based architecture, trained in an unsupervised manner to instantly enhance images. However, most Deep Learning based approaches are black-boxes and provide the user little to no insight into the enhancements applied, leaving it difficult to perform minor tweaking in enhancement as per preference. Hence, we also propose an algorithm to estimate parametric modifications given a pair of images with the aim of enabling the user more in the process of image enhancement. Together these allow complete transparency in deep learning based image enhancement while still producing results comparable to black-box approaches. We demonstrate the effectiveness of the proposed solution by comparing Mean Opinion Scores (MoS) and show that more than 84% of the users prefer the proposed solution. © 2021, Springer Nature Singapore Pte Ltd.

关键词： image enhancement

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A novel pattern matching approach on the use of multi-variant local descriptor 1

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2nd international conference on computer vision and image processing, cvip 2017

作者： Dev, Deep Suman Kisku, Dakshina Ranjan Department of Information Technology Neotia Institute of Technology Management and Science Jhinga Diamond Harbour Road Amira South 24 Parganas KolkattaWest Bengal743368 India Department of Computer Science and Engineering National Institute of Technology Durgapur DurgapurWest Bengal713209 India

ISBN: (数字)9789811078958

ISBN: (纸本)9789811078941

The objective of pattern matching problem is to find the most similar image pattern in a scene image by matching to an instance of the given pattern. For pattern matching, most distinctive features are computed from a pattern that is to be searched in the scene image. Scene image is logically divided into sliding windows of pattern size, and all the sliding windows are to be checked with the pattern for matching. Due to constant matching between the pattern and the sliding window, the matching process should be very efficient in terms of space, time and impacts due to orientation, illumination and occlusion must be minimized to obtain better matching accuracy. This paper presents a novel local feature descriptor called Multi-variant Local Binary Pattern (MVLBP) for pattern matching process while LBP is considered as base-line technique. The efficacy of the proposed pattern matching algorithm is tested on two databases and proved to be a computationally efficient one. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Local binary pattern

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Automated industrial quality control of pipe stacks using computer vision 4th

Automated industrial quality control of pipe stacks using co...

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4th international conference on computer vision and image processing, cvip 2019

作者： Chatterjee, Sayantan Chaudhuri, Bidyut B. Nandi, Gora C. Department of Robotics and Artificial Intelligence Indian Institute of Information Technology Allahabad AllahabadUttar Pradesh211012 India Department of Computer Vision and Pattern Recognition Indian Statistical Institute Kolkata KolkataWest Bengal700108 India

ISBN: (纸本)9789811540141

In this work, we describe an automated quality assurance system for pipes in warehouses and yards using simple handheld and mobile equipment like smartphone cameras. Currently, quality inspection for bent and crooked pipe ends is done manually, which entails additional labour costs and is relatively slower than a mechanised approach. We propose an efficient and robust method of detecting the perfectly circular cross-sections of the pipes in stacks using an adaptive variation of Hough Transform algorithm. As a multistage approach, our proposed method first intensifies the foreground features relative to the background and then applies Canny edge detection to obtain the gradient details. The gradient directions are in turn fed to the modified Hough Transform algorithm using Hough gradient to detect the cross-sections. The novel Hough Transform modification features a region-based processing in a "coarse to fine" manner by dividing the image into smaller grids and detecting circular cross-sections per grid, which has computational advantages of using a smaller accumulator and is less memory intensive. Experiments were performed on real industrial images to validate the efficiency of the proposed algorithm and the results show that the proposed method can successfully and accurately highlight the perfectly circular cross-sections while leaving the faulty pipe-ends undetected. © Springer Nature Singapore Pte Ltd 2020.

关键词： Hough transforms

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A novel visual secret sharing scheme using affine cipher and image interleaving

A novel visual secret sharing scheme using affine cipher and...

引用

international conference on computer vision and image processing, cvip 2016

作者： Kaur, Harkeerat Ojha, Aparajita PDPM Indian Institute of Information Technology Design and Manufacturing JabalpurMadhya Pradesh India

ISBN: (纸本)9789811021060

Recently an interesting image sharing method for gray level images using Hill Cipher and RG-method has been introduced by Chen [1]. The method does not involve pixel expansion and image recovery is lossless. However, use of Hill Cipher requires a2 × 2integermatrixwhose inverse should also be an integer matrix. Further, to extend the method for multi-secret sharing, one requires higher order integer matrices. This needs heavy computation and the choice of matrices is also very restricted, due to integer entry constraints. In the present paper we introduce an RG-based Visual Secret Sharing Scheme (VSS) scheme using image interleaving and affine cipher. Combined effect of image interleaving and affine transformation helps in improving the security of the secret images. Parameters of the affine cipher serve as keys and the random grid and encrypted image form the shares. No one can reveal the secret unless the keys and both the shares are known. Further, as opposed to the method in [1], the present scheme does not require invertible matrix with integer inverse. The scheme is also extended for multi-secret sharing. © Springer Science+Business Media Singapore 2017.

关键词： Pixels

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Generative Adversarial Network for Heritage image Super Resolution 1

引用

5th international conference on computer vision and image processing, cvip 2020

作者： Nayak, Rajashree Balabantaray, Bunil Ku. National Institute of Technology Meghalaya Shillong India

ISBN: (数字)9789811610929

ISBN: (纸本)9789811610912

In this paper we have proposed Generative Adversarial Network (GAN) based Super resolution reconstruction (SRR) method for the estimation of high resolution (HR) heritage images. The proposed SRR method via the GAN model (SRRGAN) is modeled as a min-max optimization process by integrating some new loss functions which will enable to maintain spatial and textural homogeneity in the estimated HR images. Initially, we have divided the input test image into Textured and Non-Textured patches based on their inherent characteristic followed by the optimization of the GAN model via loss functions lossTeXP and lossNonTeXP respectively to yield textured and non-textured patches of the HR image. Loss function lossTeXP helps to preserve realistic and diverse textural content of heritage images along multi-scale and multi-orientations. Whereas, lossNonTeXP efficiently preserves the complete high-frequency map of the heritage images. Consequently, the estimated HR images preserve sufficient image details with realistic textural content and reduced artifacts compared with the existing state-of-the-art SRR methods. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Generative adversarial networks

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computer vision Color Constancy from Maximal Projections Mean Assumption 7th

Computer Vision Color Constancy from Maximal Projections Mea...

引用

7th international conference on image and Signal processing (ICISP)

作者： Lakehal, Elkhamssa Ziou, Djemel Univ Batna 2 LAMIE LAMIE Lab Fac Math & Informat Fesdis Batna 05110 Algeria Univ Sherbrooke DMI Quebec City PQ Canada

ISBN: (纸本)9783319336183;9783319336176

In this paper, we propose a fast solution for the problem of illuminant color estimation. We present a physics-based algorithm that uses the mean projections maximization assumption. We investigated this hypothesis on a large images dataset and used it afterwords to estimate the illuminant color. The proposed algorithm reduces the illuminant estimation problem to an uncentred PCA problem. The evaluation of the algorithm on two well-known image datasets results in lower angular errors.

关键词： Color constancy Scene illuminant estimation Dichromatic model Principal component analysis

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Reaction-diffusion algorithm designed for image edge detection and its performance evaluation 12

Reaction-diffusion algorithm designed for image edge detecti...

引用

12th international conference on Interfaces and Human computer Interaction 2018, 11th international conference on Game and Entertainment Technologies 2018 and 12th international conference on computer Graphics, Visualization, computer vision and image processing 2018, part of the Multi conference on computer Science and Information Systems 2018, MCCSIS 2018

作者： Nomura, Atsushi Okada, Koichi Mizukami, Yoshiki Faculty of Education Yamaguchi University Yoshida 1677-1 Yamaguchi753-8513 Japan Center for the Promotion of Higher Education Yamaguchi University Yoshida 1677-1 Yamaguchi753-8511 Japan Graduate School of Science and Technology for Innovation Yamaguchi University Tokiwadai 2-16-1 Ube755-8611 Japan

ISBN: (纸本)9789898533791

The present paper proposes image edge detection algorithm utilizing a reaction-diffusion network. The network consists of two-dimensionally coupled FitzHugh-Nagumo type neurons, whose behavior is described by a set of time-evolving partial differential equations. The neurons’ non-linearity and their interconnection give the image edges through an iterative computation. The proposed algorithm differs from its previously-proposed one (Nomura et al., 2016) on the pre-processing for initializing the neurons’ state and the post-processing for thinning edges. The performance of the proposed algorithm is discussed with three image data-sets and two error measures, in comparison with performance of two other algorithms including Canny’s edge detection method. © 2018.

关键词： Neurons

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Multimodal query based approach for document image retrieval 4th

Multimodal query based approach for document image retrieval

引用

4th international conference on computer vision and image processing, cvip 2019

作者： Nandedkar, Amit V. Nandedkar, Abhijeet V. SGGS Institute of Engineering and Technology Nanded India

ISBN: (纸本)9789811540141

Scanning and storage of documents are regular practices. Retrieval of such documents is necessary to support office work. In this paper, a novel multimodal query based approach for retrieving documents using text, non-text contents is presented. This work focuses on logos, stamps, signatures for non-text query;and dates and keywords for text query to do retrieval. The proposed algorithm is called as multimodal document image retrieval algorithm (MDIRA), uses separation of text and non-text to simplify document indexing using both textual and non-textual contents. A single feature space for non-text contents is proposed for indexing. Various date formats can be recognized using regular expressions and mapped to uniform representation useful for indexing and retrieval. The proposed algorithm supports formation of multimodal queries using multiple attributes of documents. Results on a publicly available color document dataset, show the effectiveness of the proposed technique for document retrieval. © Springer Nature Singapore Pte Ltd 2020.

关键词： Indexing (of information)

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Color Based Clustering for Trunk Segmentation 25

Color Based Clustering for Trunk Segmentation

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25th international conference on Systems, Signals and image processing (IWSSIP)

作者： Czuni, Laszlo Kurtosi, Andras Ben Alaya, Karim Univ Pannonia Dept Informat Syst & Elect Engn Egyet U 10 Veszprem Hungary

ISBN: (纸本)9781538669792

While image segmentation is a fundamental and general task of image processing and computer vision, the segmentation of trunks in wood can be considered as a specific, ill posed, and hard problem. However, besides the lots of possible applications of it, the problems to be faced are general and can be found in other areas of open-air image analysis. In our paper we discuss these problems and propose a color clustering based approach as a feature generation step for the segmentation of trunks. The results of classification can be used as features for further segmentation techniques such as MRF. The possibility to apply for angle count based volume estimation is also discussed. The performance is shown through several tests with different types of wood.

关键词： Forest inventory image segmentation Clustering Logistic Model Tree k-means Angle count sampling

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