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Offline handwritten signature identification and verification using contourlet transform and support vector machine

Offline handwritten signature identification and verificatio...

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Iranian conference on Machine vision and image processing

作者： Soleymanpour, Elaheh Rajae, Boshra Pourreza, Hamid Reza Machine Vision Research Laboratory Computer Engineering Department Ferdowsi University of Mashhad Mashhad Iran

ISBN: (纸本)9781424497065

In this paper, a new method for signature identification and verification based on contourlet transform (CT) is proposed. this method uses contourlet coefficient as the feature extractor and Support Vector Machine (SVM) as the classifier. In proposed method, first signature image is normalized based on size. After preprocessing, contourlet coefficients are computed on specified scale and direction. Next, all extracted coefficients are fed to a layer of SVM classifiers as feature vector. the number of SVM classifiers is equal to the number of classes. Each SVM classifier determines if the input image belongs to the corresponding class or not. the main characteristic of proposed method is independency to nation of signers. Two experiments on two signature sets are performed. the first is on a Persian signature set and the other is on Stellenbosch (Turkish) signature set. Based on these experiments, we achieve a 100% recognition (identification) rate and more than 96.5% on Persian and Turkish signature sets respectively and 4.5% error in verification. © 2010 IEEE.

关键词： Support vector machines

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Document image segmentation using deep features 6th

Document image segmentation using deep features

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6th National conference on computer vision, Pattern Recognition, image processing and graphics, NCVPRIPG 2017

作者： Jobin, K.V. Jawahar, C.V. CVIT IIIT-Hyderabad Hyderabad India

ISBN: (纸本)9789811300196

this paper explores the effectiveness of deep features for document image segmentation. the document image segmentation problem is modelled as a pixel labeling task where each pixel in the document image is classified into one of the predefined labels such as text, comments, decorations and background. Our method first extracts deep features from superpixels of the document image. then we learn an svm classifier using these features, and segment the document image. Fisher vector encoded convolutional layer features (fv-cnn) and fully connected layer features (fc-cnn) are used in our study. Experiments validate that our method is effective and yields better results for segmenting document images in comparison to the popular approaches on benchmark handwritten datasets. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Pixels

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Contextual Self-Attention Based UNet Architecture for Fluid Segmentation in Retinal OCT B-scans 24

Contextual Self-Attention Based UNet Architecture for Fluid ...

引用

15th indian conference on computer vision graphics and image processing

作者： Kalita, Himashree Dandapat, Samarendra Bora, Prabin Kumar Indian Inst Technol Guwahati Elect & Elect Engn North Guwahati Assam India

ISBN: (纸本)9798400710759

Retinal edema caused by fluid buildups has links to vision threatening retinal diseases. Presently, spectral-domain optical coherence tomography (SD-OCT) is the imaging method of choice for evaluating retinal health and tracking treatment progress. Automated methods for fluid segmentation in retinal OCT B-scans are critical for ocular disease diagnosis. the segmentation task in retinal OCT B-scans with pathological manifestations is challenging as the retinal layered structure varies significantly with the severity of the underlying disease condition. In this paper, we present a Contextual Self-Attention based U-Net (CoSAUNet) architecture for fluid segmentation in pathological OCT B-scans. the proposed model replaces the basic convolutional layers in the standard U-Net architecture with contextual self-attention layers. the contextual self-attention mechanism integrates contextual information mining among neighboring keys and conventional self-attention into a unified architecture to learn the long-range feature dependencies. the robustness of the proposed CoSAUNet model is evaluated through a 3-fold cross-validation setup on the RETOUCH and the AROI datasets, yielding average Dice scores (DS) of 88.16% and 76.67%, respectively. Furthermore, the CoSAUNet performs comparably to the state-of-the-art methods while using only half of the parameters.

关键词： Optical coherence tomography retinal fluid segmentation deep learning semantic segmentation self-attention mechanism

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No Prompting Frozen Foundation Models: Interactive Medical Volume Segmentation using Continual Test Time Adaptation of Compact Models 24

No Prompting Frozen Foundation Models: Interactive Medical V...

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15th indian conference on computer vision graphics and image processing

作者： Borkar, Kushal Reen, Abhilaksh Singh Jawahar, C. V. Arora, Chetan Int Inst Informat Technol Hyderabad Hyderabad India Indian Inst Technol Delhi Delhi India IIIT Hyderabad Hyderabad India

ISBN: (纸本)9798400710759

Automated segmentation of medical image volumes promises to reduce costly medical experts' time for annotation. However, using machine learning for the task is challenging due to variations in imaging modalities and scarcity of patient data. While interactive image segmentation methods and foundational models incorporating user-provided prompts to refine segmentation masks have shown promise, they overlook crucial sequential information between the slices in 3D medical image volumes and videos, resulting in discontinuities in the segmentation results. this paper proposes a new framework that dynamically updates model parameters during inference in a test time training framework using user-provided scribbles. Our framework preserves acquired knowledge from the previous slices of the current medical volume and the training dataset via student-teacher learning. We evaluate our method on diverse CT, MRI, and microscopic cell datasets. Our framework significantly reduces user annotation time by a factor of 6.72x. Compared to other interactive segmentation methods, we reduce the time by a factor of 2.64x. Our method also outperforms prompting foundation models for segmentation by achieving a dice score of 0.9 in 3-4 interactions compared to 5-8 user interactions for the foundation model, significantly reducing annotation time for the CT and MRI volumes.

关键词： Medical image Analysis image Segmentation Human-computer Interaction Continual Learning

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Vote based correspondence for 3D point-set registration 12

Vote based correspondence for 3D point-set registration

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8th indian conference on computer vision, graphics and image processing, ICVGIP 2012

作者： Kulkarni, Neeraj A. Kumar, Subodh Department of Computer Science and Engineering Indian Institute of Technology Delhi India

ISBN: (纸本)9781450316606

Given two views of a static scene, estimation of correspondences between them is required for various computer vision tasks, such as 3D reconstruction and registration, motion and structure estimation, and object recognition. Without loss of generality, this paper treats the correspondence-estimation problem in the context of feature-based rangescan registration of widely separated views and presents a novel approach to obtain globally consistent set of correspondences. In this paper, we define the notion of a weak feature, and follow the approach that avoids early commitment to the "best" match. It instead considers multiple candidate matches for each feature, and eventually models and solves correspondence-estimation as an optimization problem viz. weighted bipartite matching. We focus on developing a robust approach that suceeds in the presence of significant noise and sparsity in the input. © 2012 ACM.

关键词： Object recognition

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Style-sheets Extraction from Existing Digital Contents by image processing for Web-based BML Contents Management System

Style-sheets Extraction from Existing Digital Contents by Im...

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6th International conference on computer graphics, Imaging and Visualization (CGIV 2009)

作者： Morimoto, Hidekazu Meing, Fanfan Takano, Shigeru Okada, Yoshihiro Kyushu Univ Grad Sch Informat Sci & Elect Engn Nishi Ku Fukuoka 8190395 Japan

ISBN: (纸本)9780769537894

this paper proposes a web-based BML contents management system. BML is the short form of Broadcast Markup Language which is a script language for data broadcasting contents included in digital TV broadcasting services of Japan. the scripting style of BML is very similar to that of HTML and it also supports style-sheets and JavaScript. However, in BML, there are many restrictions about the display area size, font sizes, color types and so on because the BML-browser of TV is not flexible as compared with the Web-browser. Although there are a couple of dedicated software packages for BML contents creation, they are very expensive and difficult to use. So, BML contents creation is not easy for the end-user. To make it easier to create BML contents, the authors have been developing a web-based BML contents management system. this paper explains fundamental functionalities provided by the proposed BML contents management system. Already many digital contents were created and stored and we can easily obtain their images by capturing the screen snapshot. So, this paper also proposes style-sheets extraction method for BML contents from such already existing digital contents by image processing techniques.

关键词： BML Style sheets Contentsmanagement system image processing

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3DTV view generation with virtual pan/tilt/zoom functionality 12

3DTV view generation with virtual pan/tilt/zoom functionalit...

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8th indian conference on computer vision, graphics and image processing, ICVGIP 2012

作者： Sharma, Mansi Chaudhury, Santanu Lall, Brejesh Department of Electrical Engineering Indian Institute of Technology Delhi Hauz Khas 110016 India

ISBN: (纸本)9781450316606

this paper presents a novel rendering algorithm based on depth image warping to support virtual pan-tilt-zoom (PTZ) functionalities during 3D view generation. A method based on "3D-ness" knob is proposed for automatically specifying the virtual camera positions along a path, to model the PTZ mechanism in projective framework. Two novel quality enhancing techniques based on segmentation cues are proposed to add pan, tilt and zoom capabilities during arbitrary view synthesis. In addition to reduce the computational load that results in providing such functionalities, a novel selective warping scheme is presented to reduce the computational cost by as much as 40% while maintaining an acceptable quality of rendering results. Experiments are performed using standard "Breakdancers" and "Ballet" video sequences to demonstrate the effectiveness of the proposed methods as compared to currently published results. © 2012 ACM.

关键词： three dimensional computer graphics

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computer vision and image processing 1

引用

丛书名： Communications in computer and Information Science

1000年

作者： Balasubramanian Raman Subrahmanyam Murala Abhinav Dhall Puneet Goyal Ananda Chowdhury

ISBN: (数字)9783031113499

ISBN: (纸本)9783031113482

this two-volume set (CCIS 1567-1568) constitutes the refereed proceedings of the 6h International conference on computer vision and image processing, CVIP 2021, held in Rupnagar, India, in December 2021.;the 70 full papers and 20 short papers were carefully reviewed and selected from the 260 submissions. the papers present recent research on such topics as biometrics, forensics, content protection, image enhancement/super-resolution/restoration, motion and tracking, image or video retrieval, image, image/video processing for autonomous vehicles, video scene understanding, human-computer interaction, document image analysis, face, iris, emotion, sign language and gesture recognition, 3D image/video processing, action and event detection/recognition, medical image and video analysis, vision-based human GAIT analysis, remote sensing, and more.

关键词： computer Imaging, vision, Pattern Recognition and graphics Machine Learning computer Appl. in Social and Behavioral Sciences computers and Education Information Systems Applications (incl. Internet) Database Management

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Robust Speech Recognition with Unsupervised Frame and Character Level Adversarial Domain Matching 24

Robust Speech Recognition with Unsupervised Frame and Charac...

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15th indian conference on computer vision graphics and image processing

作者： Paul, Soumen Das, Partha Pratim Rao, Krothapalli Sreenivasa Indian Inst Technol Kharagpur Dept Comp Sci & Engn Kharagpur W Bengal India

ISBN: (纸本)9798400710759

End-to-end automatic speech recognition (ASR) systems achieve promising performance for large-scale speech datasets. However, these systems experience performance degradation when a domain mismatch exists between training and test datasets. this paper addresses the domain adaptation problem by employing adversarial learning in an unsupervised manner, along with the ASR training. We propose frame level and character level domain adversarial training, which reduces the domain shift between source and target data. Frame-level adversarial training selects all source and target speech frames and tries to classify them into two domains. On the contrary, character-level training generates pseudo-labels for source and target batches and finds the feature distribution for each pseudo-character label. A random feature is selected for each character from the source and target domains. this feature set of all characters is used in the domain classification. Experiments on the Libriadapt and Librispeech clean dataset show that our approaches achieve similar word error rate (WER) reduction as for the state-of-the-art approaches with lower time complexities. the proposed approaches expect promising results for other speech adaptation applications, which will be analyzed in the future.

关键词： Adversarial learning Unsupervised domain adaptation Speech recognition

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Teaching the NAO Robot to Play a Human-Robot Interactive Game 6

Teaching the NAO Robot to Play a Human-Robot Interactive Gam...

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6th Annual conference on Computational Science and Computational Intelligence (CSCI)

作者： Li, Cen Imeokparia, Ebosehon Ketzner, Michael Tsahai, Tsega Middle Tennessee State Univ Dept Comp Sci Murfreesboro TN 37130 USA

ISBN: (纸本)9781728155845

this paper presents the background and methodologies used in programming and teaching the humanoid robot NAO to play the game of "Simon Says" with human players. Choreographe programming was used to provide the overall game logic and incorporate NAO's sensory capabilities. OpenPose pose detection and OpenCV APIs were used to develop the image processing components to convert the raw images captured by NAO for pose classification, and the Keras APIs were used to build the Convolutional Neural Network to classify and recognize the player poses.

关键词： robotics computer vision pose detection convolutional neural network image classification

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