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检索条件"任意字段=15th Indian Conference on Computer Vision Graphics and Image Processing"

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Accurate reconstruction of engineered models with surfaces of revolution 12

Accurate reconstruction of engineered models with surfaces o...

引用

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

作者： Gupta, Nithi Kumar, Subodh Indian Institute of Technology Delhi New Delhi India

ISBN: (纸本)9781450316606

Scanners and other acquisition devices are commonly used to capture shapes of real objects as point clouds. Piecewise linear approximations of point clouds are then obtained by reconstruction algorithms. Generic reconstruction algorithms rely on assumptions like smoothness, uniform or dense sampling, etc. In general, they are unable to precisely regenerate salient features of the underlying model like edges and corners. We restrict our focus to engineered models that are formed by components having simple analytically defined shapes like planes, surfaces of revolution and extrusion. We employ a parameterization that allows linearization of constraints to recover these shapes. the regularity and relationships of the components are exploited to reconstruct the accurate shape with sharp edges from highly noisy point clouds. © 2012 ACM.

关键词： computer aided design

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image-based algorithm for the catheter recognition based on GLCM 28

Image-based algorithm for the catheter recognition based on ...

引用

28th International conference on computer graphics and vision, GraphiCon 2018

作者： Danilov, V.V. Skirnevskiy, I.P. Manakov, R.A. Gerget, O.M. Melgani, F. Medical Devices Design Laboratory Tomsk Polytechnic University Tomsk Russia Signal Processing and Recognition Laboratory University of Trento Trento Italy

the focus of this study was to develop an image-based algorithm for the catheter detection. Epicardial full-volume 3D echocardiography datasets were used as an input data of the algorithm. In total, 9 datasets consisted of 15 three-dimensional timeframes were processed. To correctly detect the catheter, the feature-based approach was applied to recognition the catheter within the 3D echocardiography datasets. the algorithm based on gray-level co-occurrence matrix (GLCM) was applied as a feature extraction technique. Once the GLCM was computed, we obtained correlation, contrast, homogeneity and energy features. then we applied feature thresholds to the catheter detection. these thresholds were obtained using Support Vector Machine (SVM) with the linear kernel function and standardization the predictor data. the average segmentation and recognition accuracies of the algorithm equal 94.16% and 87.2% respectively. the processing time for one 2D slice and one 3D dataset are equal to 9±0.2 milliseconds and 1.96±0.045 seconds, respectively. though the algorithm is not time-consuming for 2D mode, it is still complicated to apply it for real-time surgery in 3D mode. © GraphiCon 2018 - 28th International conference on computer graphics and vision. All rights reserved.

关键词： Catheters

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Color image retrieval using color histogram and orthogonal combination of linear binary pattern 14

Color image retrieval using color histogram and orthogonal c...

引用

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

作者： Kaur, Kanwal Preet Singh, Chandan Bhullar, Ekta Walia Department of Computer Science Punjabi University Patiala147002 India Department of Computer Science South Asian University New Delhi110021 India

ISBN: (纸本)1595930361

Color, texture, and shape are the low level features required for an effective image retrieval system. In this paper, we propose a hybrid approach which performs the fusion of color and texture features for image retrieval. the color features are extracted by using the well known color histogram technique, while the texture features are captured using recently proposed features, known as orthogonal combination of linear binary pattern (OCLBP). the performance of the proposed approach is compared with a recently developed method, color difference histogram (CDH). Performance evaluation through extensive experiments reveals the superiority of the proposed approach over the state-of-the-art technique.

关键词： Color

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Single noisy image super resolution by minimizing nuclear norm in virtual sparse domain 6th

Single noisy image super resolution by minimizing nuclear no...

引用

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

作者： Mandal, Srimanta Rajagopalan, A.N. Image Processing and Computer Vision Lab Department of Electrical Engineering IIT Madras Chennai600036 India

ISBN: (纸本)9789811300196

Super-resolving a noisy image is a challenging problem, and needs special care as compared to the conventional super resolution approaches, when the power of noise is unknown. In this scenario, we propose an approach to super-resolve single noisy image by minimizing nuclear norm in a virtual sparse domain that tunes with the power of noise via parameter learning. the approach minimizes nuclear norm to explore the inherent low-rank structure of visual data, and is further augmented with coarse-to-fine information by adaptively re-aligning the data along the principal components of a dictionary in virtual sparse domain. the experimental results demonstrate the robustness of our approach across different powers of noise. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Optical resolving power

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A Novel Multi-Scale Residual Dense Dehazing Network (MSRDNet) for Single image Dehazingg 13

A Novel Multi-Scale Residual Dense Dehazing Network (MSRDNet...

引用

13th indian conference on computer vision, graphics, and image processing, ICVGIP 2022

作者： Manu, Chippy M. Sreeni, K.G. Computer Vision Lab Dept.Electronics and Communication College of Engineering Affiliated to APJA K.T.U Kerala Trivandrum India

ISBN: (纸本)9781450398237

Dehazing is a difficult process because of the damage caused by the non-uniform fog and haze distribution in images. To address these issues, a Multi-Scale Residual dense Dehazing Network (MSRDNet) is proposed in this paper. A Contextual feature extraction module (CFM) for extracting multi-scale features and an Adaptive Residual Dense Module (ARDN) are used as sub-modules of MSRDNet. Moreover, all the hierarchical features extracted by each ARDN are fused, which helps to detect hazy maps of varying lengths with multi-scale features. this framework outperforms the state-of-the-art dehazing methods in removing haze while maintaining and restoring image detail in real-world and synthetic images captured under various scenarios. © 2022 ACM.

关键词： image reconstruction

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A new SIFT matching criteria in a genetic algorithm framework for registering multisensory satellite imagery 14

A new SIFT matching criteria in a genetic algorithm framewor...

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

作者： Senthilnath, J. Prasad, Ram Department of Aerospace Engineering Indian Institute of Science Bangalore India Department of Electronics and Communication Engineering NITK-Surathakal Mangalore India

ISBN: (纸本)1595930361

Synthetic Aperture Radar (SAR) images are efficient and reliable source of information in extraction of damaged regions in case of floods. In assessment of damage accurately due to floods, image registration of optical (before-flood) and SAR images (after-flood) has to be carried out efficiently. In this paper, we discuss a robust multi-sensor image registration algorithm using scale invariant feature points for keypoint extraction. For matching the keypoints, a multi-objective genetic algorithm is developed with angle, distance and vicinity criterion as the fitness functions. this optimization process helps in matching the scale invariant feature points. From the obtained results, the performance of the image registration is evaluated and it is concluded that the proposed approach is efficient. Copyright 2014 ACM.

关键词： Genetic algorithms

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Scale-invariant image inpainting using gradient-based image composition 10

Scale-invariant image inpainting using gradient-based image ...

引用

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

作者： Ghorai, Mrinmoy Samanta, Soumitra Chanda, Bhabatosh Indian Statistical Institute Kolkata India

In this paper, we propose a novel scale-invariant image inpainting algorithm that combines several inpainted images obtained from multiple pyramids of different coarsest scales. To achieve this, first we build the pyramids and then we run an image inpainting algorithm individually on each of the pyramids to obtain different inpainted images. Finally, we combine those inpainted images by a gradient based approach to obtain the final inpainted image. the motivation of this approach is to solve the problem of appearing artifacts in traditional single pyramid-based approach since the results depend on the starting scale of the pyramid. Here we assume that most of the inpainted images produced by the pyramids are quite good. However, some of them may have artifacts and these artifacts are eliminated by gradient based image composition. We test the proposed algorithm on a large number of natural images and compare the results with some of the existing methods to demonstrate the efficacy and superiority of the proposed method. © Springer International Publishing AG 2017.

关键词： image processing

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TARSNet: Topology Aware Root Segmentation Network for plant phenotyping 13

TARSNet: Topology Aware Root Segmentation Network for plant ...

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13th indian conference on computer vision, graphics, and image processing, ICVGIP 2022

作者： Bhugra, Swati Mukherjee, Prerana Kaushik, Vinay Jha, Ritika Lall, Brejesh Chaudhury, Santanu Department of Electrical Engineering Indian Institute of Technology Delhi India School of Engineering Jawaharlal Nehru University India Department of Computer Science Indian Institute of Technology Jodhpur India

ISBN: (纸本)9781450398237

Root morphological traits are key to monitoring plant growth and development. Traditionally, plant biologists relied on manual or semi-Automatic approaches to accurately estimate these traits. With high-throughput acquisition of root image data, the computation of these root traits is currently achieved with automatic image analysis, and in this context, root segmentation is an important pre-processing step. However, this is a challenging task because of (1) diverse root characteristics i.e orientation, size and shape, (2) complex image background, (3) low contrast and (4) varying degrees of self-occlusion. Deep learning methods proposed for root segmentation have mainly focused on conventional pixel-wise losses. In addition, they neglected the relationship between deep features which is crucial for segmentation of thin root structures in the presence of complex backgrounds such as water droplets and leaves. In this paper, we propose a novel attention based framework that combines the strength of feature attention, topological loss and residual learning for root segmentation. the proposed framework has reached state-of-the-Art performance on Arabidopsis Root Segmentation Challenge 2021 dataset from computer vision in Plant Phenotyping and Agriculture (CVPPA). An ablation study has also been conducted to evaluate the contribution of each module to the proposed framework. © 2022 ACM.

关键词： Semantic Segmentation

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Local appearance based robust tracking via sparse representation 12

Local appearance based robust tracking via sparse representa...

引用

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

作者： Ruchandani, Avinash Babu, R. Venkatesh Indian Institute of Technology Kharagpur West Bengal India Video Analytics Lab. SERC Indian Institute of Science Bangalore Karnataka India

ISBN: (纸本)9781450316606

Visual tracking is an important task in many computer vision applications. In this paper, we present a novel approach for visual tracking using a local sparse appearance model that exploits spatial information. the sparse information along with the spatial information of local patches within this representation is used to determine the motion of the object. When the match between the target and candidate patches are represented in matrix form, the translation motion of the object can be obtained by analyzing the diagonals of the mapping matrix. A novel local template update strategy is proposed to update the relevant parts of the object within the candidate undergoing changes. Along with the local patch update, we use an adaptive/permanent template update strategy which gives less update priority to the transient local patches accounting for partial occlusion. this approach performs comparably against state-of-the-art tracking techniques, in various challenging videos involving changes in scale, pose, illumination and partial occlusion. the proposed approach tracks at a processing speed of over 40 frames per second and it is suitable for various real-time applications. © 2012 ACM.

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indian Movie Face Database: A benchmark for face recognition under wide variations

Indian Movie Face Database: A benchmark for face recognition...

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2013 4th National conference on computer vision, Pattern Recognition, image processing and graphics, NCVPRIPG 2013

作者： Setty, Shankar Husain, Moula Beham, Parisa Gudavalli, Jyothi Kandasamy, Menaka Vaddi, Radhesyam Hemadri, Vidyagouri Karure, J.C. Raju, Raja Rajan, B. Kumar, Vijay Jawahar, C.V. BVBCET Hubli India Vickramce MDU India CVIT IIITH India TCE India SDM Dharwad India PSYEC India

ISBN: (纸本)9781479915880

Recognizing human faces in the wild is emerging as a critically important, and technically challenging computer vision problem. With a few notable exceptions, most previous works in the last several decades have focused on recognizing faces captured in a laboratory setting. However, with the introduction of databases such as LFW and Pubfigs, face recognition community is gradually shifting its focus on much more challenging unconstrained settings. Since its introduction, LFW verification benchmark is getting a lot of attention with various researchers contributing towards state-of-the-results. To further boost the unconstrained face recognition research, we introduce a more challenging indian Movie Face Database (IMFDB) that has much more variability compared to LFW and Pubfigs. the database consists of 34512 faces of 100 known actors collected from approximately 103 indian movies. Unlike LFW and Pubfigs which used face detectors to automatically detect the faces from the web collection, faces in IMFDB are detected manually from all the movies. Manual selection of faces from movies resulted in high degree of variability (in scale, pose, expression, illumination, age, occlusion, makeup) which one could ever see in natural world. IMFDB is the first face database that provides a detailed annotation in terms of age, pose, gender, expression, amount of occlusion, for each face which may help other face related applications. © 2013 IEEE.

关键词： Face recognition

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