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检索条件"任意字段=Proceedings of the Fourteenth Indian Conference on Computer Vision, Graphics and Image Processing"

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Advancing Fingerprint Recognition Quality Assessment: Introducing the FRBQ Metric for Enhanced Fingerprint Recognition 23

Advancing Fingerprint Recognition Quality Assessment: Introd...

引用

proceedings of the fourteenth indian conference on computer vision, graphics and image processing

作者： Prateek Jaiswal Arka Koner Anoop Namboodiri CVIT International Institute of information technology Hyderabad IN UIDAI IN CVIT IIIT Hyderabad IN

ISBN: (纸本)9798400716256

In the field of biometric security, the quality assessment of fingerprint images is paramount for boosting the accuracy of fingerprint recognition systems. These systems are fundamental for the secure and efficient authentication and identification of individuals. Our research presents FRBQ (Fingerprint Recognition-Based Quality), an innovative quality metric designed to navigate the limitations of the NFIQ2 model. FRBQ exploits deep learning algorithms in a weakly supervised setting and utilizes matching scores from DeepPrint, a Fixed-Length Fingerprint Representation Model. Each score is paired with labels indicating the robustness of fingerprint image matches. However, in a fully referenced setting, these labels can be subjective, lacking a clear definition of what "image quality" inherently means. This weakly labeled approach strives to capture diverse perspectives on image quality, potentially making it a more encompassing metric. In comparison to NFIQ2, our research showcases the superior performance of the FRBQ model. It not only correlates better with recognition scores but also effectively evaluates challenging images that NFIQ2 struggles with. Validated by the esteemed FVC 2004 dataset, FRBQ proves its efficacy in fingerprint image quality assessment. This study underscores the transformative potential of AI in biometrics, emphasizing its capability to capture details that traditional methods might overlook. Our work stresses the critical role of precise quality assessment in the evolution of fingerprint recognition systems.

关键词： Fingerprint image Quality Fingerprint Recognition System image Quality Assessment Weakly Supervised Learning

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Lip contour detection for estimation of mouth opening area

Lip contour detection for estimation of mouth opening area

引用

National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Shreyansh Jain Prem C. Pandey Rajbabu Velmurugan Department of Electrical Engineering Indian Institute of Technology Bombay Mumbai India

In speech training aids for providing visual feedback of the articulatory efforts, time-varying vocal tract shape during speech production is generally obtained by linear prediction (LP) analysis of the speech signal and assuming a constant area at the glottis end as a reference. Its variation during speech production causes errors in the estimated vocal tract shape. The problem can be overcome by using area of the mouth opening as the reference. This area can be estimated by detecting the inner lip contour from the video recording of speaker's face during speech utterance. A technique for detection of inner lip contour, based on color transformation and template matching, is presented for reducing the errors caused by presence of teeth and tongue. Face detection by Viola-Jones algorithm, localization using a mouth detection technique, and outer lip contour detection are used to narrow down the search region for inner mouth opening. Presence of the teeth is masked by separate color transformations for upper and lower lip segments. For reducing the errors due to visibility of the tongue, which may not have any significant separation from the lips in the color space, a template matching technique is employed. It is used separately for the upper and lower lip segments to obtain the mouth opening area. The technique has been validated against graphically measured values of the mouth opening and found to be successful in estimating the mouth opening area, and it is not affected by skin hue and presence of teeth.

关键词： Teeth Estimation Speech Face Tongue Shape

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Registration of nevi in successive skin images for early detection of melanoma

Registration of nevi in successive skin images for early det...

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International conference on Pattern Recognition

作者： J. Roning M. Riech Machine Vision and Media Processing Group Infotech Oulu and Department of Electrical Engineering University of Oulu Oulu Finland

The only cure for malignant melanoma (skin cancer) is early detection. Surgical removal of a newly developed melanoma will result in complete cure. In this study, the first steps towards the development of a skin cancer detection system are reported. One possible way to detect early the occurrence of melanoma is to screen the body of a patient at regular intervals for changes or new lesions. To increase the accuracy of this laborious and painstaking task, a computer vision system could be used. One of the most important problems involved in a vision system of this kind is the need to determine which lesions in successive skin images taken over a given period, represent the same lesions. Repeated registrations of skin images also detect new lesions that do not have a counterpart on the previous image. After registration, the lesions in successive images are compared for alterations in size, shape, colour and so on, to detect changes that are suggestive of melanoma. In this paper, we introduce a new algorithm for the registration of lesions in successive skin images. The baseline algorithm requires two initial matches to register the other lesions in the images. The initial matches are provided by a physician or an algorithm that selects the most likely initial matches. The test suggests that the baseline algorithm determines 99% of the matches correctly, and this performance is largely independent of the number of lesions in the skin images.

关键词： Malignant tumors Lesions Machine vision Skin cancer Cancer detection computer vision Oncological surgery Shape Testing image registration

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Color image Super Resolution in Real Noise 18

Color Image Super Resolution in Real Noise

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proceedings of the 11th indian conference on computer vision, graphics and image processing

作者： Srimanta Mandal Kuldeep Purohit A. N. Rajagopalan DA-IICT Gandhinagar Gujarat IIT Madras Chennai Tamil Nadu

ISBN: (纸本)9781450366151

In practice, images can contain different amounts of noise for different color channels, which is not acknowledged by existing super-resolution approaches. In this paper, we propose to super-resolve noisy color images by considering the color channels jointly. Noise statistics are blindly estimated from the input low-resolution image and are used to assign different weights to different color channels in the data cost. Implicit low-rank structure of visual data is enforced via nuclear norm minimization in association with adaptive weights, which is added as a regularization term to the cost. Additionally, multi-scale details of the image are added to the model through another regularization term that involves projection onto PCA basis, which is constructed using similar patches extracted across different scales of the input image. The results demonstrate the super-resolving capability of the approach in real scenarios.

关键词： Noise

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Computational Intelligence in Pattern Recognition 1

Computational Intelligence in Pattern Recognition

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丛书名： Lecture Notes in Networks and Systems

1000年

作者： Asit Kumar Das Janmenjoy Nayak Bighnaraj Naik M. Himabindu S. Vimal Danilo Pelusi

ISBN: (数字)9789819780907

ISBN: (纸本)9789819780891

This book features high-quality research papers presented at the 6th International conference on Computational Intelligence in Pattern Recognition (CIPR 2024), held at Maharaja Sriram Chandra Bhanja Deo University (MSCB University), Baripada, Odisha, India, during March 15–16, 2024. It includes practical development experiences in various areas of data analysis and pattern recognition, focusing on soft computing technologies, clustering and classification algorithms, rough set and fuzzy set theory, evolutionary computations, neural science and neural network systems, image processing, combinatorial pattern matching, social network analysis, audio and video data analysis, data mining in dynamic environments, bioinformatics, hybrid computing, big data analytics, and deep learning. It also provides innovative solutions to the challenges in these areas and discusses recent developments.

关键词： Computational Intelligence Artificial Intelligence computer Imaging, vision, Pattern Recognition and graphics Mobile and Network Security

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New devices for 3D pose estimation: mantis eyes, Agann paintings, sundials, and other space fiducials

New devices for 3D pose estimation: mantis eyes, Agann paint...

引用

International conference on Pattern Recognition

作者： A.M. Bruckstein R.J. Holt T.S. Huang A.N. Netravali Bell Laboratories Lucent Technologies Inc. Murray Hill NJ USA Beckman Institute University of Illinois Urbana IL USA

Several unconventional ideas for viewer/camera pose estimation are discussed. The methods proposed so far advocate the use of advanced image processing for identification and precise location of calibration objects in the images acquired and base pose recovery on the identification of the viewing dependent deformations of these objects. We propose to more fully exploit the freedom in the design of "space fiducials" or calibration objects showing that we can build objects whose images directly encode, in easily identifiable gray-level/color or temporal patterns, the pose of their viewer. We also show how to construct high-precision fiducials, which can determine a viewing direction quite accurately when it is known to lie within a relatively narrow range.

关键词： Eyes Painting Electrical capacitance tomography Space technology Cameras image edge detection Calibration image processing Computational geometry computer vision

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Emerging Intelligent Computing Technology and Applications 1

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丛书名： Communications in computer and Information Science

1000年

作者： De-Shuang Huang Phalguni Gupta Xiang Zhang Prashan Premaratne

ISBN: (数字)9783642318375

ISBN: (纸本)9783642318368

This book constitutes the refereed proceedings of the 8th International conference on Intelligent Computing, ICIC 2012, held in Huangshan, China, in July 2012. The 242 revised full papers presented in the three volumes LNCS 7389, LNAI 7390, and CCIS 304 were carefully reviewed and selected from 753 submissions. The papers in this volume (CCIS 304) are organized in topical sections on Neural Networks; Particle Swarm Optimization and Niche Technology; Kernel Methods and Supporting Vector Machines; Biology Inspired Computing and Optimization; Knowledge Discovery and Data Mining; Intelligent Computing in Bioinformatics; Intelligent Computing in Pattern Recognition; Intelligent Computing in image processing; Intelligent Computing in computer vision; Intelligent Control and Automation; Knowledge Representation/Reasoning and Expert Systems; Advances in Information Security; Protein and Gene Bioinformatics; Soft Computing and Bio-Inspired Techiques in Real-World Applications; Bio-Inspired Computing and Applications.

关键词： Artificial Intelligence Algorithm Analysis and Problem Complexity Information Systems Applications (incl. Internet) Computation by Abstract Devices Pattern Recognition computer Communication Networks

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Estimation of discrete curvature based on chain-code pairing and digital straightness

Estimation of discrete curvature based on chain-code pairing...

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IEEE International conference on image processing

作者： Shyamosree Pal Partha Bhowmick Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India

Estimation of discrete curvature is a challenging problem, since a mere replacement of functional derivatives by numerical differences fails to produce the desired result. Several algorithms have been proposed so far, which are mostly based on the concepts of real geometry and hence are computationally expensive. The existing measure of k-curvature, though easy to compute, is crippled with some unwanted syndromes arising out of improper consideration of chain codes. Hence, an improved algorithm for estimating k-curvature is proposed, which is marked by its inherent simplicity and computational attractiveness, and produces the expected estimate, whether the concerned point has an extreme (high or low) curvature or the concerned segment has a constant or changing curvature. Examples and experimental results demonstrate the fitness and effectiveness of the proposed technique for digital curves of arbitrary shapes.

关键词： Shape Application software image analysis Surface fitting computer science Computational geometry image processing computer graphics computer vision Embossing

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Modelling and restoration of multilook correlated speckled images

Modelling and restoration of multilook correlated speckled i...

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IEEE International conference on image processing

作者： M. Aggarwal U.B. Desai Department of Electrical Engineering Indian Institute of Technology Mumbai India

A model for the speckle process is proposed based on the underlying phenomena, which can take into account correlation present in radar images. The restoration problem is then formulated using the Bayesian framework. The new model is found to give significantly better results for correlated speckled images as compared to models which disregard correlation.

关键词： image restoration Speckle Pixel Radar imaging Integrated circuit modeling Bayesian methods Synthetic aperture radar Radar polarimetry computer vision Lattices

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LEDNet: Deep Network for Single image Haze Removal 2018

LEDNet: Deep Network for Single Image Haze Removal

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proceedings of the 11th indian conference on computer vision, graphics and image processing

作者： Akshay Dudhane Subrahmanyam Murala Abhinav Dhall Computer Vision and Pattern Recognition Lab Indian Institute of Technology Ropar India Learning Affect and Semantic Image Analysis Group Indian Institute of Technology Ropar India

ISBN: (纸本)9781450366151

Haze during the bad weather, degrades the visibility of the scene drastically. Degradation of scene visibility varies with respect to the transmission coefficient/map (Tc) of the scene. Estimation of accurate Tc is key step to reconstruct the haze free scene. Previously, local as well as global priors were proposed to estimate the Tc. We, on the other hand, propose integration of local and global approaches to learn both point level and object level Tc. The proposed local encoder decoder network (LEDNet) estimates the scene transmission map in two stages. During first stage, network estimates the point level Tc using parallel convolutional filters and spatial invariance filtering. The second stage comprises of a two level encoder-decoder architecture which anticipates the object level Tc. We also propose, local air-light estimation (LAE) algorithm, which is able to obtain the air-light component of the outdoor scene. Combination of LEDNet and LAE improves the accuracy of haze model to recover the scene radiance. Structural similarity index, mean square error and peak signal to noise ratio are used to evaluate the performance of the proposed approach for single image haze removal. Experiments on benchmark datasets show that LEDNet outperforms the existing state-of-the-art methods for single image haze removal.

关键词： Haze removal transmission map CNN

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