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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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Singer Based Classification of Song Dataset Using Vocal Signature Inherent in Signal 5

Singer Based Classification of Song Dataset Using Vocal Sign...

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

作者： Sarkar, Rajib Saha, Sanjoy Kumar Jadavpur Univ Dept Comp Sci & Engn Kolkata India

ISBN: (纸本)9781467385640

Singer based classification of song data is important in the applications like, organized archival and indexing of music data, music retrieval. In a song, singing voice is mixed with accompanying instrument signal. To extract the vocal characteristics of the singer, the effect of non-voiced part is to be minimized. In this work a simple methodology is proposed to remove the non-voiced segments and to reduce the impression of instruments from the voice-dominating signal. To extract the vocal signature, proposed features extract the variation pattern of zero crossing rate and short term energy. In broad sense, the features try to capture the range of pitch and energy over which a singer mostly operates. this is motivated by the way a human being tries to identify a singer. Finally, singer based classification is done using multi-layer perceptron network. Experiment is carried out with artist 20 dataset and 63% classification accuracy is achieved. Comparison with reported works on the same dataset shows that the performance of the proposed simple methodology is better than the majority and very close to others.

关键词： singer identification time domain filtering frequency domain filtering STE and ZCR based feature MFCC

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Multi-resolution image Fusion Using Multistage Guided Filter

Multi-resolution Image Fusion Using Multistage Guided Filter

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

作者： Joshi, Sharad Upla, Kishor P. Joshi, Manjunath V. SV Natl Inst Technol Surat 395007 Gujarat India Dhirubhai Ambani Inst Informat & Commun Technol Gandhinagar 382007 Gujarat India

ISBN: (纸本)9781479915880

In this paper, we propose a multi-resolution image fusion approach based on multistage guided filter (MGF). Given the high spatial resolution panchromatic (Pan) and high spectral resolution multi-spectral (MS) images, the multi-resolution image fusion algorithm obtains a single fused image having both the high spectral and the high spatial resolutions. Here, we extract the missing high frequency details of MS image by using multistage guided filter. the detail extraction process exploits the relationship between the Pan and MS images by utilizing one of them as a guidance image and extracting details from the other. this way the spatial distortion of MS image is reduced by consistently combining the details obtained using both types of images. the final fused image is obtained by adding the extracted high frequency details to corresponding MS image. the results of the proposed algorithm are compared with the commonly used traditional methods as well as with a recently proposed method using Quickbird, Ikonos-2 and Worldview-2 satellite images. the quantitative assessment is evaluated using the conventional measures as well as using a relatively new index i. e., quality with no reference (QNR) which does not require a reference image. the results and measures clearly show that there is significant improvement in the quality of the fused image using the proposed approach.

关键词： MULTISTAGE image fusion images Multi-resolution imagery (Psychotherapy) image Filters peroxyacetyl nitrate Mass spectroscopy Multiple Sclerosis

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Implementation of the "Local Rank Differences" image Feature Using SIMD Instructions of CPU

Implementation of the "Local Rank Differences" Image Feature...

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

作者： Herout, Adam Zemcik, Pavel Juranek, Roman Hradis, Michal Brno Univ Technol Graph FIT Brno Czech Republic

ISBN: (纸本)9781424442195

Usage of statistical classifiers, namely AdaBoost and its modifications, in object detection and pattern recognition is a contemporary and popular trend the computatiponal performance of these classifiers largely depends on low level image features they are using: both from the point of view of the amount of information the feature provides and the executional time of its evaluation. Local Rank Difference is an image feature that is alternative to commonly used Haar features. It is suitable for implementation in programmable (FPGA) or specialized (ASIC) hardware as well as graphics hardware (GPU). Additionally, as shown in this paper, it performs very well on common CPU's. the paper discusses the LRD features and their properties, describes an experimental implementation of LRD using the multimedia instruction set of current general-purpose processors, presents its empirical performance measures compared to alternative approaches, and suggests several notes on practical usage of LRD and proposes directions for future work.

关键词： Adaptive boosting

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Extraction of Line-Word-Character Segments Directly from Run-Length Compressed Printed Text-Documents

Extraction of Line-Word-Character Segments Directly from Run...

引用

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

作者： Javed, Mohammed Nagabhushan, P. Chaudhuri, B. B. Univ Mysore Dept Studies Comp Sci Mysore 570006 Karnataka India Indian Stat Inst Comp Vis & Pattern Recognit Unit Kolkata 700108 India

ISBN: (纸本)9781479915880

Segmentation of a text-document into lines, words and characters, which is considered to be the crucial preprocessing stage in Optical Character Recognition (OCR) is traditionally carried out on uncompressed documents, although most of the documents in real life are available in compressed form, for the reasons such as transmission and storage efficiency. However, this implies that the compressed image should be decompressed, which indents additional computing resources. this limitation has motivated us to take up research in document image analysis using compressed documents. In this paper, we think in a new way to carry out segmentation at line, word and character level in run-length compressed printed-text-documents. We extract the horizontal projection profile curve from the compressed file and using the local minima points perform line segmentation. However, tracing vertical information which leads to tracking words-characters in a run-length compressed file is not very straight forward. therefore, we propose a novel technique for carrying out simultaneous word and character segmentation by popping out column runs from each row in an intelligent sequence. the proposed algorithms have been validated with 1101 text-lines, 1409 words and 7582 characters from a data-set of 3 5 noise and skew free compressed documents of Bengali, Kannada and English Scripts.

关键词： Compressed document segmentation run-length compression Line word and character segmentation

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Dementia Disease Progression Analysis from 2D Cellular Automata Architecture 24

Dementia Disease Progression Analysis from 2D Cellular Autom...

引用

15th indian conference on computer vision graphics and image processing

作者： Kesu, Siva Manohar Reddy Sinha, Neelam Ramasangu, Hariharan Inst Sci Campus Ctr Brain Res Indian Bangalore Karnataka India Relecura Bangalore Karnataka India

ISBN: (纸本)9798400710759

the detection of change in mild cognitive impairment (MCI) is vital between one visit and another visit for the early-stage detection of Alzheimer's disease (AD). It is associated with changes in the structural and functional aspects. Diagnosis of dementia progression is a challenging but essential step for the planning of early treatment. this paper proposes the cellular automata (CA) framework to identify the changes when the disease progresses from one visit to another. An updated rule using the conduction function of anisotropic diffusion has been proposed to assess the earliest signs of dementia manifestation and progression. the progression of dementia disease in multi-visit subjects for healthy and unhealthy patients has been analyzed by examining the entropy from evolved 2D CA images. the subjects below the reference line in healthy cases lead to the prognosis of the disease, whereas subjects above the reference line in unhealthy subjects are in improved condition. the proposed CA architecture shows the transitions and progressive patterns, thereby offering a method for tracking the evolution of dementia over time.

关键词： Dementia Functional Connectivity FMRI Cellular Automata Disease Progression

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PALM LEAF MANUSCRIPT/COLOR DOCUMENT image ENHANCEMENT BY USING IMPROVED ADAPTIVE BINARIZATION MEthOD

PALM LEAF MANUSCRIPT/COLOR DOCUMENT IMAGE ENHANCEMENT BY USI...

引用

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

作者： Cherala, Sridhar Rege, Priti Coll Engn Pune Maharashtra India

ISBN: (纸本)9781424442195

this paper presents a new color document image binarization that is suitable for palm leaf manuscripts and color document images. the proposed method consists of two steps: a pre-processing procedure using low-pass Wiener filter, and contrast adaptive binarization for segmentation of text from the background. Firstly, in the pre-processing stage, low-pass Wiener filter is used to eliminate noisy areas, smoothing of background texture as well as contrast enhancement between background and text areas. Finally, binarization is performed by using contrast adaptive binarization method in order to extract useful text information from low quality document images. the techniques are tested on a set of palm leaf manuscript images/color document images. the performance of the algorithm is demonstrated on by palm leaf manuscripts/color documents distorted with show-through effects, uneven background color and localized spot.

关键词： binarization pre-processing contrast adaptive binarization palm leaf manuscript/color document images

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Colour Retinal image Enhancement based on Domain Knowledge

Colour Retinal Image Enhancement based on Domain Knowledge

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

作者： Joshi, Gopal Datt Sivaswamy, Jayanthi IIIT Hyderabad Ctr Visual Informat Technol Hyderabad Andhra Pradesh India

ISBN: (纸本)9781424442195

Retinal images are widely used to manually or automatically detect and diagnose many diseases. Due to the complex imaging setup, there is a large luminosity and contrast variability within and across images. Here, we use the knowledge of the imaging geometry and propose an enhancement method for colour retinal images, with a focus on contrast improvement with no introduction of artifacts. the method uses non-uniform sampling to estimate the degradation and derive a correction factor from a single plane. We also propose a scheme for applying the derived correction factor to enhance all the colour planes of a given image. the proposed enhancement method has been tested on a publicly available dataset [8]. Results show marked improvement over existing methods.

关键词： image enhancement

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IDA-UIE: An Iterative Framework for Deep Network based Degradation Aware Underwater image Enhancement 24

IDA-UIE: An Iterative Framework for Deep Network based Degra...

引用

15th indian conference on computer vision graphics and image processing

作者： Singh, Pranjali Guha, Prithwijit Indian Inst Technol Guwahati Ctr Intelligent Cyber Phys Syst Gauhati Assam India Indian Inst Technol Guwahati Dept Elect & Elect Engn Gauhati Assam India

ISBN: (纸本)9798400710759

Underwater image quality is often compromised due to factors like fluorescence, low illumination, absorption, and scattering. Recent advancements in underwater image enhancement have introduced various deep network architectures to address these issues. Typically, these methods employ a single network to tackle all degradation challenges. However, we hypothesize that deep networks trained for specific conditions outperform those trained for multiple degradation cases. Consequently, we propose an iterative framework that individually identifies and resolves a dominant degradation condition. We focus on eight specific degradation conditions: low illumination, low contrast, haziness, blurriness, noise, and color imbalances across three channels. Our approach involves designing a deep network capable of detecting the dominant degradation condition and selecting an appropriate deep network tailored for that specific condition. We further propose that our work is the creation of condition-specific datasets derived from high-quality images in two standard datasets, UIEB and EUVP. these datasets facilitate the training of enhancement networks specific to each degradation condition. Our proposed method performs better than the nine baseline methods on both UIEB and EUVP datasets.

关键词： Underwater Imaging Model Deep Learning Underwater image Enhancement

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Real-time Simulation of Human Musculature 11

Real-time Simulation of Human Musculature

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

作者： Kanjilal, Neeladrishekhar Chaudhuri, Parag Indian Inst Technol Dept Comp Sci & Engg Mumbai Maharashtra India

ISBN: (纸本)9781450366151

We present a reduced model based on position based dynamics for real-time simulation of human musculature. We demonstrate our methods on the muscles of the human arm. Co-simulation of all the muscles of the human arm allow us to accurately track the development of stresses and strains in the muscles, when the arm is moved. We evaluate our method for accuracy by comparing it with gold standard simulation models based on finite volume methods, and demonstrate the stability of the method under flexion, extension and torsion.

关键词： Human muscle simulation position based dynamics shape matching

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Parametric Video Compression Scheme using AR based Texture Synthesis

Parametric Video Compression Scheme using AR based Texture S...

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

作者： Khandelia, Aditya Gorecha, Saurabh Lall, Brejesh Chaudhury, Santanu Mathur, Mona Indian Inst Technol Dept Elect Engn Delhi India

ISBN: (纸本)9781424442195

In this paper a video coding scheme based on parametric compression of texture is proposed Each macro block is characterized either as an edge block, or as a non edge block containing texture. the non edge blocks are coded by modeling them as an auto-regressive process (AR). By applying the AR model in spatio-temporal domain, we ensure both spatial as well as temporal consistency. Edge blocks are encoded using the standard H.264/AVC. the proposed algorithm achieves upto 54.52% more compression as compared to the standard H.264/AVC at similar visual quality.

关键词： Video signal processing

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