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Techniques for improving the performance of image retrieval using relevance feedback 14

Techniques for improving the performance of image retrieval ...

引用

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

作者： Nayak, Shrikant Sekhar, C. Chandra Department of Computer Science and Engineering Indian Institute of Technology Madras India

ISBN: (纸本)1595930361

Relevance feedback is important in bridging the semantic gap between the low-level visual features and the high-level semantic concepts during the image retrieval. In this work, the image retrieval using relevance feedback involves four phases. In the first phase, an initial retrieval is carried out for a given query image and each of the retrieved images is rated as relevant or irrelevant. In the second phase, the rated images are clustered. In the third phase, a score is computed for each image in the repository to measure the degree of its relevance to the query using the images in the clusters. We propose a method to compute the score using the local relevance feedback and the global relevance feedback. The local relevance feedback based component of the score is computed using the instance-based feedback approach. In this approach, the degree of relevance is measured using the feedback from the current iteration only. The global relevance feedback based component of the score is computed using the query-point movement approach. In this approach, the degree of relevance is measured using the feedback from different iterations. The scores for the images in the repository are used to retrieve the images. Each of the newly retrieved images is rated as relevant or irrelevant. In the fourth phase, each of the newly rated images is assigned to an existing cluster of rated images. We propose to represent an irregularly shaped cluster using multiple representatives. These representatives are used to assign each of the newly rated images to a cluster. The third and fourth phases are repeated until there is a convergence of the process of retrieval. The image retrieval performance for the proposed methods is compared with that of the existing methods on Wang and Corel image datasets. Results of these studies demonstrate the effectiveness of the proposed methods in improving the retrieval performance. Copyright 2014 ACM.

关键词： image retrieval

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HDR-cGAN: Single LDR to HDR image translation using conditional GAN 21

HDR-cGAN: Single LDR to HDR image translation using conditio...

引用

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

作者： Raipurkar, Prarabdh Pal, Rohil Raman, Shanmuganathan CVIG Lab IIT Gandhinagar Gujarat India

ISBN: (纸本)9781450391276

The prime goal of digital imaging techniques is to reproduce the realistic appearance of a scene. Low Dynamic Range (LDR) cameras are incapable of representing the wide dynamic range of the real-world scene. The captured images turn out to be either too dark (underexposed) or too bright (overexposed). Specifically, saturation in overexposed regions makes the task of reconstructing a High Dynamic Range (HDR) image from single LDR image challenging. In this paper, we propose a deep learning based approach to recover details in the saturated areas while reconstructing the HDR image. We formulate this problem as an image-to-image (I2I) translation task. To this end, we present a novel conditional GAN (cGAN) based framework trained in an end-to-end fashion over the HDR-REAL and HDR-SYNTH datasets. Our framework uses an overexposed mask obtained from a pre-trained segmentation model to facilitate the hallucination task of adding details in the saturated regions. We demonstrate the effectiveness of the proposed method by performing an extensive quantitative and qualitative comparison with several state-of-the-art single-image HDR reconstruction techniques. © 2021 ACM.

关键词： Generative adversarial networks

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A novel unsupervised thresholding technique for landsat image change detection 21

A novel unsupervised thresholding technique for landsat imag...

引用

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

作者： Gupta, Neha Ari, Samit Mishra, Anoop Kumar VIT-AP University Andhra Pradesh Amaravati India National Institute of Technology Odisha Rourkela India

ISBN: (纸本)9781450391276

Thresholding is the most widely used change detection technique for identifying the changes in remote sensing images. However, most of the thresholding methods would generate isolated spots in the final change map, which are reduced by applying postprocessing step. This paper proposes a novel thresholding technique to address the aforesaid problem without applying the postprocessisng operation. The proposed technique uses two thresholds simultaneously to generate the change map, which is the key point of this method. Above-stated thresholds are calculated by initial indicators that are generated by local neighborhood mutual information. In addition, this approach compares the local statistics of the interested pixel with the derived thresholds instead of the pixel itself, which enhances the robustness of this technique. Particularly, the method resides on three things: generation of initial indicators, use of two thresholds simultaneously, and comparison of local statistics with thresholds. Finally, the method is tested on multitemporal multispectral images of different sensors, and experimental results validate the effectiveness of the proposed method. © 2021 ACM.

关键词： K-means clustering

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Dense captioning for Text-image ReID 14

Dense captioning for Text-Image ReID

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14th indian conference on computer vision, graphics and image processing, ICVGIP 2023

作者： Subramanyam, A.V. Sundararajan, Niranjan Dubey, Vibhu Lall, Brejesh IIITD India IITD India

ISBN: (纸本)9798400716256

Text-to-image (T2I) ReID has attracted a lot of attention in the recent past. CUHK-PEDES, RSTPReid and ICFG-PEDES are the three available benchmarks to evaluate T2I ReID methods. RSTPReid and ICFG-PEDES comprise of identities from MSMT17 but due to limited number of unique persons, the diversity is limited. On the other hand, CUHK-PEDES comprises of 13,003 identities but has relatively shorter text description on average. Further, these datasets are captured in a restricted environment with limited number of cameras. In order to further diversify the identities and provide dense captions, we propose a novel dataset. Our dataset comprises of 20,000 unique identities captured in the wild and provides a rich dataset for text-to-image ReID. With a minimum of 26 words for a description, each image is densely captioned. We further synthetically generate images and fine-grained captions using Stable-diffusion and BLIP models trained on our dataset. We perform elaborate experiments using state-of-art text-to-image ReID models and vision-language pre-trained models and present a comprehensive analysis of the dataset. Our experiments also reveal that synthetically generated data leads to a substantial performance improvement in both same dataset as well as cross dataset settings. We will release the code and dataset. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Benchmark Synthetic data Text-to-image ReID

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Robust Watermarking Scheme Based on Multiresolution Fractional Fourier Transform

Robust Watermarking Scheme Based on Multiresolution Fraction...

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Gaurav Bhatnagar Balasubramanian Raman Department of Mathematics Indian Institute of Technology Roorkee Roorkee India

In this paper, a new robust watermarking scheme is proposed in multiresolution fractional Fourier transform domain using singular value decomposition. The watermark is embedded in the high frequency sub-band of the host image at coarsest level. Although the schemes based on SVD are robust but fail under ambiguity attacks. In this attack, both the owner and attacker can extract their watermark from the watermarked image. To prevent ambiguity, the normalized mass matrix is formed and embedded in the host image. In extraction, normalized mass matrix is extracted first and compared with original one. If the similarity is found then the singular values are extracted to construct the watermark. Experimental evaluation demonstrates that the proposed scheme is able to withstand a variety of attacks.

关键词： Robustness Watermarking Fourier transforms Spatial resolution Frequency domain analysis Discrete transforms Signal resolution Time frequency analysis image resolution Mathematics

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Anisotropic Diffusion and Segmentation of Colored Flowers

Anisotropic Diffusion and Segmentation of Colored Flowers

引用

indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Shoma Chatterjee Department of Computer Science and Engineering Jaypee Institute of Information Technology Noida Uttar Pradesh India

This paper presents a new anisotropic diffusion method for multi-valued images. The colored flowers are segmented from the background. In my diffusion technique the edge stopping function is computed as inversely proportional to the weighted sum of gradients of color components. The value of edge stopping function tends to zero as the weighted sum of three color gradients becomes large. The other algorithm further explores an existing diffusion technique based on structure tensors. The multivalued image diffuses using a system of coupled differential equations in the direction of minimal change. The paper presents the results of anisotropic diffusion and segmentation of colored flowers. The new method can also be applied for anisotropic diffusion of other multivalued images.

关键词： Anisotropic magnetoresistance image segmentation computer science Smoothing methods Tensile stress image edge detection Color Information technology Differential equations Robustness

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Design and Implementation of a Robust Palm Biometrics Recognition and Verification System

Design and Implementation of a Robust Palm Biometrics Recogn...

引用

indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Saurabh Parashar Anand Vardhan C. Patvardhan Prem Kumar Kalra Dayalbagh Educational Institute (Deemed University) Agra India Indian Institute of Technology New Delhi India

Complete design and implementation of a robust palm biometrics recognition and verification system has been presented. The paper attempts to scientifically develop a comprehensive set of hand geometry features and develop an original algorithm from a fundamental level to robustly compute a selected set of features so as to minimize palm placement effect. These features are combined with chrominance features, to achieve recognition and verification accuracy, significant with respect to the current state in palm biometrics research. The algorithm has been kept robust, simple and computationally efficient while the implementation is relatively inexpensive. The experiments on recognition, Principal Components Analysis (PCA) and verification, on a dataset of 100 users strongly confirm the utility of robustly calculating a comprehensive set of scientifically selected hand geometry features. The results uncover the potential of hand geometry features and confirm that the system can be used in medium to high security environments.

关键词： Robustness Biometrics Geometry Principal component analysis image recognition Fingerprint recognition Geometrical optics image databases computer vision computer graphics

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A tweak on k-nearest neighbor decision rule

A tweak on k-nearest neighbor decision rule

引用

2012 International conference on image processing, computer vision, and Pattern Recognition, IPCV 2012

作者： Basu, Tanmay Murthy, C.A. Chakrabarty, Himadri Machine Intelligence Unit Indian Statistical Institute 203 B. T. Road Kolkata-700108 India Department of Computer Scinece Surendranath College University of Calcutta Kolkata - 700009 India

ISBN: (纸本)9781601322258

The k-nearest neighbor (knn) decision rule puts a point into a particular class if the class has the maximum representation among the k nearest neighbors of the point in the training set. If the difference between the number of points belonging to the two competing classes (i.e., two classes with maximum representation) among the k nearest neighbors is at least one then the point will be assigned to that class. This article presents a tweak on the knn rule to enhance the confidence of the knn voting process. This method proposes a discrimination criterion on the majority voting of knn by a predefined threshold to enhance the rigidity of the voting process. The method does not require the knowledge of neighborhood parameter k to execute knn. The empirical studies show the utility of the proposed method using some synthetic and well known benchmark data sets. It is observed from the experiments that the accuracy of the proposed method is significantly better than the traditional knn method.

关键词： Pattern recognition

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Unsupervised Domain Adaptation for Remote Sensing images Using Metric Learning and Correlation Alignment 7th

Unsupervised Domain Adaptation for Remote Sensing Images Usi...

引用

7th National conference on computer vision, Pattern Recognition, image processing, and graphics, NCVPRIPG 2019

作者： Mahapatra, Aniruddha Banerjee, Biplab Indian Institute of Technology Roorkee India Indian Institute of Technology Bombay Mumbai India

ISBN: (纸本)9789811586965

We address the problem of domain adaptation (DA) in the context of remote sensing (RS) image classification in this paper. By definition, the problem of unsupervised DA aims at classifying samples from a target domain which is strictly devoid of any label information while assuming that enough training data are available from a related yet non-identical (in terms of data distributions) source domain. A number of existing approaches in this regard are focused towards matching the underlying distributions of the data from both the domains in a shared latent space without explicitly considering: i) the discriminativeness of the embedding space, ii) the usefulness of a manifold distance is pulling the domains towards each other over the standard Euclidean measures. However, we argue the importance of both the aspects in learning the latent space, particularly for fine-grained classes. Our model jointly optimizes both the terms in an end-to-end fashion and the learned latent space is found to properly align the classes with high precision. Experimental results obtained on a hyper-spectral and a multi-spectral dataset confirm the superior performance of the approach over a number of techniques from the literature. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Remote sensing

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Trajectory based integrated features for action classification from depth data 6th

Trajectory based integrated features for action classificati...

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

作者： Shukla, Parul Arora, Noopur Biswas, Kanad K. Indian Institute of Technology Delhi India Works Application Singapore Singapore Bennett University Greater NoidaUttar Pradesh India

ISBN: (纸本)9789811300196

We present an approach for Human Action Recognition based on amalgamation of features from depth maps and body-joint data. This Integrated feature set consists of depth features based on gradient orientation and motion energy, in addition to features from 3D- skeleton data capturing its statistical details. Feature selection is carried out to extract a relevant set of features for action recognition. The resultant set of features are evaluated using SVM classifier. We validate our proposed method on various benchmark datasets for Action Recognition such as MSR-Daily Activity and UT-Kinect dataset. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Metals

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