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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"

共 1495 条记录，以下是1211-1220 订阅

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Multi-font telugu text recognition using hidden Markov models and Akshara Bi-grams 10

Multi-font telugu text recognition using hidden Markov model...

引用

10th indian conference on computer vision, graphics and image processing, ICVGIP 2016

作者： Devarapalli, Koteswara Rao Negi, Atul Department of Computer Science and Engineering Mahatma Gandhi Institute of Technology Hyderabad500075 India School of Computer and Information Sciences University of Hyderabad Gachibowli Hyderabad500046 India

Recent advances in the information technology made possible to introduce many Unicode Telugu fonts for the documentation needs of present society. But the recognition of documents printed in a variety of fonts poses new challenges in building Telugu OCR systems. In this paper, we demonstrate multi-font Telugu printed word recognition using implicit segmentation approach that provides segmentation as a by-product of recognition. Our word recognition approach relies on Hidden Markov Models and akshara bi-gram language model to recognize word images in terms of aksharas (characters). The training set of word images is prepared from document images of popular books and the synthetic document images generated using 8 different Unicode fonts. The testing involves matching the feature vector sequence against sequence of akshara HMMs based on bi-grams. The CER and WER of this system are 21% and 37% respectively. The performance of our system is very encouraging. © Springer International Publishing AG 2017.

关键词： Hidden Markov models

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A novel approach for image dehazing combining visible-NIR images

A novel approach for image dehazing combining visible-NIR im...

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

作者： Ashish V. Vanmali Samrudha G. Kelkar Vikram M. Gadre Department of Electrical Engineering Indian Institute of Technology Bombay Powai Mumbai India

image dehazing either using single visible image or using visible and near-infrared (NIR) image pair has seen growing interest in last decade for improving visibility in landscape photographs. In this paper, we propose a novel approach for image dehazing scheme using a pair of visible and NIR images. The dehazing mechanism estimates depth map and airlight color using the visible-NIR scene statistics and uses them to form a haze-free image. Experiments on a variety of hazy images demonstrate that our method achieves high degree of detail recovery over the existing image dehazing algorithms. The resultant images exhibit a very good blend of details, contrast and color. The proposed algorithm is less computationally demanding and is fully automatic. The results are superior in both visual as well as quantitative analysis compared to state-of-the-art image dehazing algorithms.

关键词： image color analysis Estimation Color Channel estimation Attenuation Databases Algorithm design and analysis

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Statistical Video Tracking of Pomegranate Fruits

Statistical Video Tracking of Pomegranate Fruits

引用

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

作者： Ankush Roy Suvadeep Banerjee Debayan Roy Anupam Mukhopadhyay CVPR Unit Indian Statistical Institute Kolkata India Department of Electrical Engineering Jadavpur University Kolkata India

Efficient location of fruits in the trees is the most important criterion of an automatic robotic harvesting system. The main challenges faced in the development of the robotic harvesting arm are accurate identification of the fruits in dense foliages and detection of the occluded fruits. This paper proposes a statistical technique that accurately detects and tracks pomegranates in trees. A k-means clustering methodology is implemented as a preprocessor step followed by image analysis algorithms that finally locate the fruit accurately under varying conditions of illumination, human intervention, camera view etc. The simplicity of the technique is attributed to its real-time capability to detect and track fruits in a video of fruit-bearing trees. The ground truth data were computed on 25 video sequences and the system was tested on another 25 videos. The detection efficiency is as high as 96.3%.

关键词： image color analysis Cameras Robots Lighting Accuracy Streaming media Shape

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MP-FEG: Media Player controlled by Facial Expressions and Gestures

MP-FEG: Media Player controlled by Facial Expressions and Ge...

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

作者： Swapna Agarwal Saiyed Umer Electronics and Communication Sciences Unit Indian Statistical Institute Kolkata

In this paper we represent a new technique to interact with the computer in a non-tangible way. Specifically we have designed a Media Player system controller by Facial Expressions and Gestures (MP-FEG). We detect and track one landmark point on the finger and 18 landmark points on the lips to capture the movement of the finger and the lips of the user. The movement patterns are classified into hand gestures and facial expressions using support vector machine (SVM). We have achieved ~98.65% and ~100% recognition accuracies for hand-gestures and facial expressions respectively. Occurrence of each of these actions (5 hand-gesturs and 3 facial expressions) is associated with a command to control (e.g., to select, play, pause the video) the video player. Perceptional quality analysis by user survey rates the experience of the non-tangible human-computer-interaction facilited by the proposed technique as `good'.

关键词： Feature extraction Face recognition Support vector machines computers Media Lips Gesture recognition

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Complementary Cumulative Precision Distribution: A New Graphical Metric for Medical image Retrieval System

Complementary Cumulative Precision Distribution: A New Graph...

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conference on Medical Imaging - image Perception, Observer Performance, and Technology Assessment

作者： Dash, Jatindra Kumar Mukhopadhyay, Sudipta Khandelwal, Niranjan Indian Inst Technol Dept Elect & Elect Commun Engn Kharagpur 721302 W Bengal India Post Grad Inst Med Educ & Res Chandigarh India

ISBN: (纸本)9780819498304

Several single valued measures have been proposed by researchers for the quantitative performance evaluation of medical image retrieval systems. Precision and recall are the most common evaluation measures used by researchers. Amongst graphical measures proposed, precision vs. recall graph is the most common evaluation measure. Precision vs. recall graph evaluates different systems by varying the operating points (number of top retrieval considered). However, in real life the operating point for different applications are known. Therefore, it is essential to evaluate different retrieval systems at a particular operating point set by the user. None of the graphical metric provides the variation of performance of query images over the entire database at a particular operating point. This paper proposes a graphical metric called Complementary Cumulative Precision Distribution (CCPD) that evaluates different systems at a particular operating point considering each images in the database for query. The strength of the metric is its ability to represent all these measures pictorially. The proposed metric (CCPD) pictorially represents the different possible values of precision and the fraction of query images at those precision values considering number of top retrievals constant. Different scalar measures are derived from the proposed graphical metric (CCPD) for effective evaluation of retrieval systems. It is also observed that the proposed metric can be used as a tie breaker when the performance of different methods are very close to each other in terms of average precision.

关键词： Content based image retrieval retrieval performance performance metric precision complementary cumulative precision distribution recall complementary cumulative recall distribution

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Moment and curvature preserving technique for accurate ellipse boundary detection

Moment and curvature preserving technique for accurate ellip...

引用

International conference on Pattern Recognition

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

Circles and their elliptic projections are very commonly used image features in computer vision applications. Thus, it is very important to be able to determine their location in an accurate manner. A technique for determining an ellipse boundary with subpixel precision is proposed. The technique, called the moment and curvature preserving detection (MCP), utilizes the first three intensity moments and the intensity gradient of the image. The idea of using moments for subpixel edge detection is not new, but in the case of ellipses the moments do not provide sufficient information for precise detection. However, if the local curvature is augmented to the observations, the ellipse boundary can be determined reliably.

关键词： image edge detection computer vision Application software Cameras Face detection Detectors Machine vision Feature extraction Calibration Pixel

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A Schrödinger formalism for simultaneously computing the Euclidean distance transform and its gradient density 14

A Schrödinger formalism for simultaneously computing the Eu...

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9th indian conference on computer vision, graphics and image processing, ICVGIP 2014

作者： Gurumoorthy, Karthik S. Rangarajan, Anand International Center for Theoretical Sciences Tata Institute of Fundamental Research Bangalore Karnataka India Department of Computer and Information Science and Engineering University of Florida GainesvilleFL United States

ISBN: (纸本)1595930361

In this work, we employ the well-known Hamilton-Jacobi to Schrödinger connection to present a unified framework for computing both the Euclidean distance function and its gradient density in two dimensions. Previous work in this direction considered two different formalisms for independently computing these quantities. While the two formalisms are very closely related, their lack of integration is theoretically troubling and practically cumbersome. We introduce a novel Schrödinger wave function for representing the Euclidean distance transform from a discrete set of points. An approximate distance transform is computed from the magnitude of the wave function while the gradient density is estimated from the Fourier transform of the phase of the wave function. In addition to its simplicity and efficient O(N logN) computation, we prove that the wave function-based density estimator increasingly, closely approximates the distance transform gradient density (as a free parameter approaches zero) with the added benefit of not requiring the true distance function. Copyright 2014 ACM.

关键词： Wave functions

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indian Regional Sign Language Recognition 23

Indian Regional Sign Language Recognition

引用

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

作者： Sujatha C Madhura K Patil Umadevi. F.M Neha Jain Akshata Badni Ranjeeta Angadi Shankar Gangisetty Computer Science and Engineering KLE Technological University INDIA Computer Science and Engineering KLE Technological University Hubballi INDIA Computer Science and Engineering IIIT Hyderabad INDIA

ISBN: (纸本)9798400716256

Sign Language is a medium of communication in the Deaf and Hard of Hearing community (DHH community). According to WHO, there are approximately 63 million people in India, including 3.3 million from the state of Karnataka, with 0.3 million children belonging to DHH community. The sign language gestures vary globally, making communication difficult between the DHH community and others. Hence, Sign Language Recognition has gained significant attention in recent years. There is a limited publicly available dataset on indian Sign Language. In addition, the dataset for regional languages especially the Kannada dataset, is unavailable for the sign recognition tasks. Hence initially, in our work, we built a dataset of indian Regional Kannada Sign Language (IRKSL) for different levels of data at character, word, and sentence levels. We propose a method for recognizing the indian sign language and translating it into Kannada regional language. We demonstrate the proposed method on the IRKSL dataset and obtained an accuracy of 81.69% and 73.87% with and without feature augmentation, respectively, on the IRKSL dataset. We also evaluated our work on the INCLUDE 50 dataset and obtained a better accuracy of 93.42% as compared to the state-of-art method.

关键词： Attention based BiLSTM CNN Feature Augmentation indian Sign Language Recognition

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Worst-Case Adversarial Perturbation and Effect of Feature Normalization on Max-Margin Multi-label Classifiers 12th

Worst-Case Adversarial Perturbation and Effect of Feature No...

引用

12th indian conference on computer vision, graphics, and image processing, ICVGIP 2021

作者： Gupta, Ritesh Kumar Verma, Yashaswi Pvt Ltd. Noida India IIT Jodhpur India

ISBN: (纸本)9789811941351

Multi-label classification is a generalization of single-label classification, where an unseen sample is automatically assigned a subset of semantically relevant labels from a given vocabulary. In parallel, recent research has demonstrated the impact of adversarial examples, which are modifications of original samples and aim at fooling machine learning models. Unlike existing adversary generation techniques which are specific to single-label data and mostly assume the availability of training data and/or model to the attacker, in this paper, we propose a generalized adversary generation mechanism by generating worst-case perturbation. This perturbation, when added to the feature vector of the original sample, generates an adversarial sample without the need for the availability of either training data or model to the attacker. Next, for the first time as per our knowledge, we study and demonstrate the effect of feature normalization as a defense mechanism against adversarial attacks. Extensive experiments show the effectiveness of our adversarial attack and defense mechanisms using state-of-the-art max-margin multi-label classification algorithms on two benchmark datasets. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： image annotation

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Intelligent Interactive Technologies and Multimedia 1

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丛书名： Communications in computer and Information Science

1000年

作者： Anupam Agrawal R. C. Tripathi M. D. Tiwari Ellen Yi-Luen Do

ISBN: (数字)9783642374630

ISBN: (纸本)9783642374623

This book constitutes the refereed proceedings of the Second International conference on Intelligent Interactive Technologies and Multimedia, IITM 2013, held in Allahabad, India, in March 2013. The 15 revised full papers and the 12 revised short papers were carefully reviewed and selected from more than 90 submissions. The papers present the latest research and development in the areas of intelligent interactive technologies, human-computer interaction and multimedia.

关键词： image processing and computer vision User Interfaces and Human computer Interaction Information Storage and Retrieval Artificial Intelligence

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