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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 1494 条记录，以下是131-140 订阅

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Invariance Properties of AM-FM image Features with Application to Template Tracking

Invariance Properties of AM-FM Image Features with Applicati...

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6th indian conference on computer vision, graphics and image processing

作者： Prakash, R. Senthil Aravind, R. Indian Inst Technol Dept Elect Engn Madras 600036 Tamil Nadu India

ISBN: (纸本)9781424442195

AM-FM models analyze an image in terms of amplitude and frequency modulated sinusoids. Such models are well suited to describe the local non-stationarities of an image. In this paper the invariance of AM-FM features with respect to scaling, rotation and illumination changes is presented. These properties can be used in applications of AM-FM image models where features for affine transformed images need to be computed. The application of invariance properties in template tracking is illustrated using a particle filter based tracker that uses the AM-FM features.

关键词： Frequency modulation

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Removal of Hand-drawn Annotation Lines from Document images by Digital-geometric Analysis and Inpainting

Removal of Hand-drawn Annotation Lines from Document Images ...

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4th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Pratihar, Sanjoy Bhowmick, Partha Sural, Shamik Mukhopadhyay, Jayanta Indian Inst Technol Dept Comp Sci & Engn Kharagpur 721302 W Bengal India Indian Inst Technol Sch Informat Technol Kharagpur 721302 W Bengal India

ISBN: (纸本)9781479915880

Performance of an OCR system is badly affected due to presence of hand-drawn annotation lines in various forms, such as underlines, circular lines, and other text-surrounding curves. Such annotation lines are drawn by a reader usually in free hand in order to summarize some text or to mark the keywords within a document page. In this paper, we propose a generalized scheme for detection and removal of these handdrawn annotations from a scanned document page. An underline drawn by hand is roughly horizontal or has a tolerable undulation, whereas for a hand-drawn curved line, the slope usually changes at a gradual pace. Based on this observation, we detect the cover of an annotation object-be it straight or curvedas a sequence of straight edge segments. The novelty of the proposed method lies in its ability to compute the exact cover of the annotation object, even when it touches or passes through any text character. After getting the annotation cover, an effective method of inpainting is used to quantify the regions where text reconstruction is needed. We have done our experimentation with various documents written in English, and some results are presented here to show the efficiency and robustness of the proposed method.

关键词： ANNOTATIONS hand-drawn inpaint STRAIGHT-EDGE document image lines lines texts

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Non-rigid Registration using Spectral Graph Wavelet Features 11

Non-rigid Registration using Spectral Graph Wavelet Features

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11th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Thottupattu, Alphin J. Yadav, Shivin Sharma, Avinash Int Inst Informat Technol Hyderabad India

ISBN: (纸本)9781450366151

image registration is an essential step in many computer vision applications which demands high accuracy for significantly random and complex deformations. In medical image processing applications image registration is a basic preprocessing step to non-rigidly align images from different acquisition environments to an atlas image. We propose a novel non-rigid image registration method to get more reliable registration even under noisy conditions with manageable time complexity. The proposed method explores the the inherent multi-resolution capability of wavelets to perform nonrigid registration in a graph environment. The inherent time complexity of wavelet feature map calculation is avoided using Chebyshev Polynomial approximations for the wavelet operators.

关键词： image registration

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Integrated Algorithm for Different Tracking Challenges 5

Integrated Algorithm for Different Tracking Challenges

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5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Shah, Jay Sai Subrahmanyam, G. R. K. Mishra, Deepak Indian Inst Space Sci & Technol Dept Avion Trivandrum 695547 Kerala India Indian Inst Space Sci & Technol Dept Earth & Space Sci Trivandrum 695547 Kerala India

ISBN: (纸本)9781467385640

This paper presents an efficient combination of two well-known tracking algorithms, Tracking-Learning-Detection (TLD) and Compressive Tracking (CT) to devise an algorithm which takes advantages of both and outperforms them on their short-ends by virtue of other. TLD fails in cases including full out-of-plane rotation, fast motion and articulated object tracking. While CT fails in resuming tracking once the object leaves the frame and comes back. We propose a combining algorithm mentioned as Algorithm 1, which robustly handles all the tracking challenges. Different thresholds are set which can be varied to weigh each component as required. The proposed algorithm is tested on different test sequences involving challenging tracking scenarios such as fast motion and their success rates are calculated in Table I. The proposed algorithm works favourably against both algorithms in terms of robustness and success rate.

关键词： Tracking (position)

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An Optimal Underwater image Enhancement based on Fuzzy Gray World Algorithm and Bacterial Foraging Algorithm 5

An Optimal Underwater Image Enhancement based on Fuzzy Gray ...

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5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Sethi, Rajni Sreedevi, Indu Verma, O. P. Jain, Veni Delhi Technol Univ CSE Dept Delhi India Delhi Technol Univ ECE Dept Delhi India CPA Global Noida Uttar Pradesh India

ISBN: (纸本)9781467385640

Underwater images suffer from non uniform contrast and poor visibility due to bad illumination and color cast in deep water. Such images have a hazy and color diminished appearance making underwater studies a difficult task. Researches in last decades performed color correction, assuming that underwater images have bluish color cast which is not always true. In this paper, a new image enhancement approach is proposed which modifies the gray world algorithm by finding the color cast using fuzzy logic and then removing the color cast by optimizing the correction method using Bacterial Foraging Optimisation (BFO). Proposed approach is adaptive in nature as it finds the intensity of color cast instead of assuming it which improves the quality of underwater images. Computed results have enhanced visual details, contrast and color performance.

关键词： image Enhancement Fuzzy logic Gray World Assumption Multiobjective BFO Underwater images Color correction

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Generic Action Recognition from Egocentric Videos 5

Generic Action Recognition from Egocentric Videos

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5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Singh, Suriya Arora, Chetan Jawahar, C. V. IIIT Hyderabad CVIT Hyderabad Andhra Pradesh India IIIT Delhi New Delhi India

ISBN: (纸本)9781467385640

Egocentric cameras are wearable cameras mounted on a person's head or shoulder. With their ability to have first person view, such cameras are spawning new set of exciting applications in computer vision. Recognising activity of the wearer from an egocentric video is an important but challenging problem. The task is made especially difficult because of unavailability of wearer's pose as well as extreme camera shake due to motion of wearer's head. Solutions suggested so far for the problem, have either focussed on short term actions such as pour, stir etc. or long term activities such as walking, driving etc. The features used in both the styles are very different and the technique developed for one style often fail miserably on other kind. In this paper we propose a technique to identify if a long term or a short term action is present in an egocentric video segment. This allows us to have a generic first-person action recognition system where we can recognise both short term as well as long term actions of the wearer. We report an accuracy of 90.15% for our classifier on publicly available egocentric video dataset comprising 18 hours of video amounting to 1.9 million tested samples.

关键词： Cameras

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image Defencing via Signal Demixing 16

Image Defencing via Signal Demixing

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

作者： Kumar, Veepin Mukherjee, Jayanta Das Mandal, Shyamal Kumar Indian Inst Technol Ctr Educ Technol Kharagpur 721302 W Bengal India Indian Inst Technol Dept Comp Sci & Engn Kharagpur 721302 W Bengal India

ISBN: (纸本)9781450347532

We present a novel algorithm to remove near regular, fence or wire like foreground patterns from an image. The fence detection or fence removal algorithms, developed so far, have poor performance in detecting the fence. We use signal demixing to utilize the sparsity and regularity property of fences to detect them. Results demonstrate the effectiveness of our technique as compared to other state of the art techniques.

关键词： Object detection fence removal image inpainting signal demixing

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Bishnupur Heritage image Dataset (BHID): A resource for various computer vision applications 16

Bishnupur Heritage Image Dataset (BHID): A resource for vari...

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

作者： Ghorai, Mrinmoy Purkait, Pulak Santra, Sanchayan Samanta, Soumitra Chanda, Bhabatosh Indian Stat Inst Kolkata India Adelaide Univ Adelaide SA Australia

ISBN: (纸本)9781450347532

Bishnupur is an attractive tourist place in West Bengal, India and is known for its terracotta temples. The place is one of the prospective candidates to be included in the list of UNESCO World Heritage sites. We intend to preserve this heritage site digitally and also to present some virtual interaction for the tourist and researchers. In this paper, we present an image dataset of different temples (namely, Jor Bangla, Kalachand, Madan Mohan, Radha Madhav, Rasmancha, Shyamrai and Nandalal) in Bishnupur for evaluating different types of computer vision and image processing algorithms (like 3D reconstruction, image inpainting, texture classification and content specific image retrieval). The dataset is captured using four different cameras with different parameter settings. Some datasets are extracted and earmarked for certain applications such as texture classification, image inpainting and content specific image retrieval. Example results of baseline methods are also shown for these applications. Thus we evaluate the usefulness of this dataset. To the best of our knowledge, probably this is the first attempt of combined dataset for evaluating various types of problems for a heritage site in India.

关键词： Heritage data SFM image inpainting temple texture

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Diagnosis of Pomegranate Plant Diseases using Neural Network 5

Diagnosis of Pomegranate Plant Diseases using Neural Network

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5th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Dhakate, Mrunmayee Ingole, A. B. SPPU Sinhgad Acad Engn Dept E&TC Pune Maharashtra India

ISBN: (纸本)9781467385640

Pomegranate is a fruit which grows with a very high yield in many states of India and one of the most profits gaining fruit in the market. But due to various conditions, the plants are infected by various diseases which destroy the entire crop leaving very less product yield. So, the work proposes an image processing and neural network methods to deal with the main issues of phytopathology i.e. disease detection and classification. The Pomegranate fruit as well as the leaves are affected by various diseases caused by fungus, bacteria and the climatic conditions. These diseases are like Bacterial Blight, Fruit Spot, Fruit rot and Leaf spot. The system uses some images for training, some for testing purpose and so on. The color images are pre-processed and undergo k-means clustering segmentation. The texture features are extracted using GLCM method, and given to the artificial neural network. The overall accuracy of this method is 90%. The results are proved to be accurate and satisfactory in contrast to manual grading and hopefully take a strong rise in establishing itself in the market as one of the most efficient process.

关键词： disease detection and classification pomegranate plant diseases k-means clustering segmentation GLCM method artificial neural network

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Adaptive BPSO based Feature Selection and Skin Detection based Background Removal for Enhanced Face Recognition

Adaptive BPSO based Feature Selection and Skin Detection bas...

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4th National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Sattiraju, Mayukh Vikram, Manikandan M. Manikantan, K. Ramachandran, S. MS Ramaiah Inst Tech Dept Elect & Commun Engn Bangalore 560054 Karnataka India SJB Inst Tech Dept Elect & Commun Engn Bangalore 560060 Karnataka India

ISBN: (纸本)9781479915880

Face recognition under varying background and pose is challenging, and extracting background and pose invariant features is an effective approach to solve this problem. This paper proposes a skin detection-based approach for enhancing the performance of a Face Recognition (FR) system, employing a unique combination of Skin based background removal, Discrete Wavelet Transform (DWT), Adaptive Multi-Level Threshold Binary Particle Swarm Optimization (ABPSO) and an Error Control Feedback (ECF) loop. Skin based background removal is used for efficient background removal and ABPSO-based feature selection algorithm is used to search the feature space for the optimal feature subset. The ECF loop is used to neutralize pose variations. Experimental results, obtained by applying the proposed algorithm on Color FERET and CMUPIE face databases, show that the proposed system outperforms other FR systems. A significant increase in the recognition rate and substantial reduction in the number of features are observed.

关键词： Face Recognition image Preprocessing Feature Selection Particle Swarm Optimization

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