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Light-aware luminance adaptive enhancement network for RGBT video object detection

Light-aware luminance adaptive enhancement network for RGBT ...

引用

2024 international conference on computer vision and image processing, cvip 2024

作者： Ma, Shuchen Jiang, Yafei Gao, Liuxuanqi Li, Yipei Han, Baojing SDIC FINANCE Co. Ltd. Beijing100032 China School of Computer Science and Technology Anhui University Hefei230039 China Shanxi Yitong Power Grid Protection Automation Co. Ltd. Taiyuan030025 China State Grid Shanxi Electric Power Company Taiyuan030025 China

ISBN: (纸本)9781510688384

Visible-thermal Video Object Detection (RGBT VOD) aims to detect objects in RGB and thermal video sequences and predict their categories and locations. One of the core aspects of this task is how to efficiently and effectively perform the fusion of multiple modalities. Due to the limitations of the imaging mechanism, under poor lighting conditions, the image quality of the RGB modality will dramatically decline, reducing the detection performance. Supplementing with thermal data can effectively mitigate these challenges. To fully utilize the complementary information of the two modalities, existing works on feature fusion of RGB and thermal images require an extremely complex modality interaction process, which is time and resource-intensive. When converting the data of the two modalities to the YCbCr color space represented by luminance and color, only luminance information exists in the thermal image. In contrast, the RGB image is rich in luminance and color information. However, due to the imaging mechanism, the luminance information of the RGB modality can easily be affected by bad lighting. To simplify the design of the multimodal interaction module, reduce model complexity, and take full advantage of complementary multimodal information, we consider multi-modality fusion in terms of luminance information for multimodal data and propose a Light-aware Luminance Adaptive Enhancement Network (LA2ENet). Specifically, we design a Light-aware Luminance Adaptive Enhancement Module (LA2EM), which can sense the light information in the scene. When the luminance information in the RGB image is drastically affected due to bad lighting, the module will adaptively introduce the luminance information in the stabilized thermal infrared image to supplement and improve the quality of the RGB image. After that, we only use the luminance-enhanced RGB image as the input to the model, making full use of the modal complementary information while reducing the complexity of the model.

关键词： Video recording

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Workpiece inspection system based on zoom lens

Workpiece inspection system based on zoom lens

引用

2024 international conference on computer vision and image processing, cvip 2024

作者： Wang, Wenke Wang, Xiaofei Guan, Chen Zhao, Bing Fan, Hua Qilu University of Technology Shandong Academy of Sciences Jinan250000 China

ISBN: (纸本)9781510688384

With the rapid development of industrial technology, metal materials are widely used in production and daily life. More and more parts and workpieces are produced from factory assembly lines, and they are applied in different fields due to their different functions. However, with the increase of production, the traditional detection methods have been unable to keep up with the speed of production, and can not meet the growing detection requirements. In order to detect the products produced quickly and efficiently, new detection methods must be introduced. This study designs a workpiece detection system that integrates shooting, size measurement, and surface defect detection using a variable zoom lens. The system consists of hardware and control components. The hardware part uses the zoom lens instead of the ordinary lens to realize the zoom function of the monocular camera, so that the device can shoot the focal plane of different focal lengths. The control part can be divided into image acquisition, image processing, size measurement and defect detection. The system is mainly used in the detection of workpieces with two or more focal planes, because in reality, the workpiece with a single focal plane only accounts for a small part of all the workpieces, and most of the workpieces or parts have multiple focal planes. An experimental device was made by using the zoom lens, industrial camera, stage and light source used in the laboratory. In the study, the images captured by the industrial camera were used to obtain clear images of multiple focal planes by image definition algorithm and image fusion algorithm. Based on this image, the size measurement and defect detection of the workpiece were carried out. The experimental results show that the system can realize the clear imaging of multiple focal planes of the workpiece by using the zoom lens, and can realize the size measurement and defect detection of the workpiece on this basis. The system has potential applicati

关键词： image acquisition

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Proceedings of international conference on computer vision and image processing 1st ed. 2017

引用

丛书名： Advances in Intelligent Systems and Computing

2017年

作者： Balasubramanian Raman Sanjeev Kumar Partha Pratim Roy Debashis Sen

ISBN: (数字)9789811021077

ISBN: (纸本)9789811021060

This edited volume contains technical contributions in the field of computer vision and image processing presented at the First international conference on computer vision and image processing (cvip 2016). The contributions are thematically divided based on their relation to operations at the lower, middle and higher levels of vision systems, and their applications. The technical contributions in the areas of sensors, acquisition, visualization and enhancement are classified as related to low-level operations. They discuss various modern topics reconfigurable image system architecture, Scheimpflug camera calibration, real-time autofocusing, climate visualization, tone mapping, super-resolution and image resizing. The technical contributions in the areas of segmentation and retrieval are classified as related to mid-level operations. They discuss some state-of-the-art techniques non-rigid image registration, iterative image partitioning, egocentric object detection and video shot boundary detection. The technical contributions in the areas of classification and retrieval are categorized as related to high-level operations. They discuss some state-of-the-art approaches extreme learning machines, and target, gesture and action recognition. A non-regularized state preserving extreme learning machine is presented for natural scene classification. An algorithm for human action recognition through dynamic frame warping based on depth cues is given. Target recognition in night vision through convolutional neural network is also presented. Use of convolutional neural network in detecting static hand gesture is also discussed. Finally, the technical contributions in the areas of surveillance, coding and data security, and biometrics and document processing are considered as applications of computer vision and image processing. They discuss some contemporary applications. A few of them are a system for tackling blind curves, a quick reaction target acquisition and tracking sys

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Road Surface Classification Using Texture Synthesis Based on Gray-Level Co-occurrence Matrix

Road Surface Classification Using Texture Synthesis Based on...

引用

1st international conference on computer vision and image processing (cvip)

作者： Mukherjee, Somnath Pandey, Saurabh Kritikal Solut Pvt Ltd Comp Vis & Image Proc Unit Bangalore Karnataka India

ISBN: (纸本)9789811021046;9789811021039

Advance Driving Assistance System (ADAS) has been a growing area of interest in the research community for automotive domain where scene understanding and modeling is one of the principally focus area of activities. Texture synthesis using gray-level co-occurrence matrix (GLCM) of any rigid body is not an exceptional task in image processing area. The additional integration of this method is for texture characterization and use it for the road surface classifications which is the primary focus of this paper. We have also introduced that GLCM based road surface analysis in a line scan manner that can be used as a module for ADAS application.

关键词： Gray-level co-occurrence matrix Road texture The Advance Driving Assistance System (ADAS) etc

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A Hybrid Method for image Categorization Using Shape Descriptors and Histogram of Oriented Gradients

A Hybrid Method for Image Categorization Using Shape Descrip...

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1st international conference on computer vision and image processing (cvip)

作者： Agrawal, Subhash Chand Jalal, Anand Singh Tripathi, Rajesh Kumar GLA Univ Dept Comp Engn & Applicat Mathura India

ISBN: (纸本)9789811021046;9789811021039

image categorization is the process of classifying all pixels of an image into one of several classes. In this paper, we have proposed a novel vision-based method for image categorization is invariant to affine transformation and robust to cluttered background. The proposed methodology consists of three phases: segmentation, feature extraction, and classification. In segmentation, an object of interest is segmented from the image. Features representing the image are extracted in feature extraction phase. Finally, an image is classified using multi-class support vector machine. The main advantage of this method is that it is simple and computationally efficient. We have tested the performance of proposed system on Caltech 101 object category and reported 76.14 % recognition accuracy.

关键词： Segmentation K-means clustering Histogram of oriented gradients Shape descriptors Codebook

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A Local Correlation and Directive Contrast Based image Fusion

A Local Correlation and Directive Contrast Based Image Fusio...

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1st international conference on computer vision and image processing (cvip)

作者： Sonam Kumar, Manoj Babasaheb Bhimrao Ambedkar Univ Dept Comp Sci Lucknow Uttar Pradesh India

ISBN: (纸本)9789811021046;9789811021039

In this paper, a local correlation and directive contrast-based multi-focus image fusion technique is proposed. The proposed fusion method is conducted into two parts. In first part, Discrete Wavelet Packet Transform (DWPT) is performed over the source images, by which low and high frequency coefficients are obtained. In second part, these transformed coefficients are fused using local correlation and directive contrast-based approach. The performance of the proposed method is tested on several pairs of multi-focus images and compared with few existing methods. The experimental results demonstrate that the proposed method provides better results than other existing methods.

关键词： image fusion Discrete wavelet packet transform Directive contrast Peak-signal-to-noise-ratio Correlation coefficient Standard deviation

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Multi-exposure image Fusion Using Propagated image Filtering

Multi-exposure Image Fusion Using Propagated Image Filtering

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1st international conference on computer vision and image processing (cvip)

作者： Patel, Diptiben Sonane, Bhoomika Raman, Shanmuganathan Indian Inst Technol Elect Engn Gandhinagar India

ISBN: (纸本)9789811021046;9789811021039

image fusion is the process of combining multiple images of a same scene to single high-quality image which has more information than any of the input images. In this paper, we propose a new fusion approach in a spatial domain using propagated image filter. The proposed approach calculates the weight map of every input image using the propagated image filter and gradient domain postprocessing. Propagated image filter exploits cumulative weight construction approach for filtering operation. We show that the proposed approach is able to achieve state-of-the-art results for the problem of multi-exposure fusion for various types of indoor and outdoor natural static scenes with varying amounts of dynamic range.

关键词： Computational photography Multi-exposure fusion HDR imaging Propagated image filter

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PARALLEL SCALABLE LIBRARIES AND ALGORITHMS FOR computer vision 12

PARALLEL SCALABLE LIBRARIES AND ALGORITHMS FOR COMPUTER VISI...

引用

conference C on Signal processing and conference D on Parallel Computing, at the 12th IAPR international conference on Pattern Recognition

作者： JAMIESON, LH DELP, EJ HAMBRUSCH, SE KHOKHAR, AA COOK, GW HAMEED, F PATEL, JN SHEN, K PURDUE UNIV DEPT ELECT ENGNW LAFAYETTEIN 47907

ISBN: (纸本)0818662751

We describe a project that integrates applications requirements, parallel algorithm design, models of parallel computing, and software tools in order to improve the ability of applications researchers in the fields of computer vision and image processing (cvip) to realize the performance potential of high performance parallel computers. This objective is achieved by pursuing four directions of research: the development of efficient and practical scalable algorithms for fundamental cvip problems;the implementation of realistic cvip scenarios on high performance computers;the development of a scalable, architecture-independent parallel model and a metric for estimating the performance of an algorithm on an existing parallel machine;and the development of prototype software tools. In this paper we describe work in each of these areas. © 1994 IEEE.

关键词： computer vision

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A Hybrid Method Based CT image Denoising Using Nonsubsampled Contourlet and Curvelet Transforms

A Hybrid Method Based CT Image Denoising Using Nonsubsampled...

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1st international conference on computer vision and image processing (cvip)

作者： Diwakar, Manoj Kumar, Manoj Babasaheb Bhimrao Ambedkar Univ Dept Comp Sci Lucknow Uttar Pradesh India

ISBN: (纸本)9789811021046;9789811021039

Computed tomography (CT) is one of the most widespread radio-logical tools for diagnosis purpose. To achieve good quality of CT images with low radiation dose has drawn a lot of attention to researchers. Hence, post-processing of CT images has become a major concern in medical image processing. This paper presents a novel edge-preserving image denoising scheme where noisy CT images are denoised using nonsubsampled contourlet transform (NSCT) and curvelet transform separately. By estimating variance difference on both denoised images, final denoised CT image has been achieved using a variation-based weighted aggregation. The proposed scheme is compared with existing methods and it is observed that the performance of proposed method is superior to existing methods in terms of visual quality, image quality index (IQI), and peak signal-to-noise ratio (PSNR).

关键词： image denoising Wavelet transform Curvelet transform Nonsub-sampled contourlet transform Thresholding

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Fast Non-blind image Deblurring with Sparse Priors

Fast Non-blind Image Deblurring with Sparse Priors

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1st international conference on computer vision and image processing (cvip)

作者： Das, Rajshekhar Bajpai, Anurag Venkatesan, Shankar M. Samsung R&D Inst 2870 Phoenix BldgBagmane Constellat Business Pk Bengaluru India

ISBN: (纸本)9789811021046;9789811021039

Capturing clear images in dim light conditions remains a critical problem in digital photography. Long exposure time inevitably leads to motion blur due to camera shake. On the other hand, short exposure time with high gain yields sharp but noisy images. However, exploiting information from both the blurry and noisy images can produce superior results in image reconstruction. In this paper, we employ the image pairs to carry out a non-blind deconvolution and compare the performances of three different deconvolution methods, namely, Richardson Lucy algorithm, Algebraic deconvolution, and Basis Pursuit deconvolution. We show that the Basis Pursuit approach produces the best results in most cases.

关键词： Basis pursuit Richardson Lucy Non-blind deconvolution Compressed sensing Deblurring

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