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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems XII"

共 12901 条记录，以下是251-260 订阅

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Automated Detection and Analysis of Road Cracks and Pothole Depths using Computer Vision and Depth Imaging 15

Automated Detection and Analysis of Road Cracks and Pothole ...

引用

15th International conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Makkena, Manohar Lingamallu, Geyani Digavalli, Veda Harshitha Gudupalli, Vamshidhar Reddy Manikandan, V.M. Panchikkil, Shaiju Srm University-AP Andhra Pradesh India

ISBN: (纸本)9798350370249

Maintaining road infrastructure is essential to effective transportation systems and public safety. This research provides a new method for pothole depth estimation and automatic road crack detection using computer vision techniques. Our method utilizes convolutional neural networks (CNNs) for classifying road images into 'With Crack' or 'Without Crack' categories with high accuracy. Additionally, we employ image processing algorithms to detect and highlight cracks, providing insights into their lengths and percentages. Furthermore, we introduce a monocular depth estimation model to assess pothole depths, aiding in prioritizing road repair efforts. Experimental results demonstrate the effectiveness of our approach in accurately identifying road defects and estimating their severity. This research contributes to the advancement of intelligent infrastructure management systems, enabling proactive maintenance and ensuring safer roads for communities. © 2024 IEEE.

关键词： CNN Heat Map image Analysis image Classification Monocular depth estimation

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Identification of Polycystic Ovary Syndrome in ultrasound images of Ovaries using Distinct Threshold based image Segmentation

Identification of Polycystic Ovary Syndrome in ultrasound im...

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2023 International conference on Advancement in Computation and Computer Technologies, InCACCT 2023

作者： Poorani, B. Khilar, Rashmita SIMATS University Saveetha School of Engineering Department of Computer Science Engineering Thandalam Chennai India

ISBN: (纸本)9798350396485

Polycystic Ovary Syndrome (PCOS) is a common hormonal disorder among women of reproductive age and it can lead to infertility, metabolic disorders and other health problems. Ultrasound is an important tool for the diagnosis of PCOS. In medical image processing, the threshold segmentation plays a critical role in the identification of PCOS by isolating and accurately analyzing the cysts. In this paper, the PCOMorphology is extracted from the ultrasound images using three threshold-based segmentation algorithms: Adaptive Mean Threshold, Adaptive Gaussian Threshold, and Otsu Threshold. The performance of these algorithms is evaluated based on several metrics such as accuracy, sensitivity, specificity, and F1 score. The results show that the Otsu Threshold algorithm provides the best performance in terms of follicle detection and accuracy, followed by Adaptive Gaussian Threshold and Adaptive Mean Threshold. In conclusion, the comparison of these three algorithms shows that Otsu Threshold algorithm is the most suitable for the identification of PCOS using ultrasound images. The results of this study have important implications for the diagnosis of PCOS and further research is needed to improve the accuracy of the diagnosis. The proposed algorithms can be integrated into the existing clinical diagnosis systems to improve the accuracy and efficiency of the diagnosis process. This study provides a promising direction for future research in the field of medical image processing and PCOS diagnosis © 2023 IEEE.

关键词： image segmentation

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Adaptive analysis of rapid prediction of coal quality information based on image analysis

Adaptive analysis of rapid prediction of coal quality inform...

引用

2022 International conference on Computer Graphics, Artificial Intelligence, and Data processing, ICCAID 2022

作者： Liu, Ming Zhang, Hua CHN Energy Xinjiang Chemical Co. Ltd. Xinjiang Urumqi831404 China

ISBN: (纸本)9781510663350

Machine vision technology has shown great potential for development and application in the coal heat utilization and coal chemical production process It is important to carry out image analysis-based stability adaptation analysis of coal heat utilization and coal chemical equipment. To further expand its application, this work reviewed the characteristics of different vision sensor systems and image processing algorithms in the process of image acquisition and processing, conducted applicability analysis for rapid prediction of coal quality, presented the current problems and future development trends of image analysis technology in the coal heat utilization and coal chemical production process. It provided theoretical guidance and reference for promoting automation, intelligence, and mechanization in the coal industry. © 2023 SPIE.

关键词： Forecasting

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Real-Time Obstacle Detection and Path Adjustment for Autonomous Robots Using OpenCV

Real-Time Obstacle Detection and Path Adjustment for Autonom...

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2024 International conference on Telecommunications and Intelligent systems, ICTIS 2024

作者： Elaoua, Abrar Nadour, Mohamed Cherroun, Lakhmissi Mahdi, Mohammed Taqiyeddine Hafaifa, Ahmed Djelfa Algeria

ISBN: (纸本)9798331527396

The real-time obstacle detection and path adjustment system for autonomous robots presented in this paper was created using OpenCV. The combination of image processing techniques enables the robot to identify and navigate around any obstacle efficiently. The main functions include real-time image acquisition;where the robot constantly takes pictures of its surroundings, and obstacle detection;which uses edge detection and contour analysis for proper identification of hazards in the environment. The method entails that once an object is detected, the robot's route is reshaped with sophisticated algorithms that are aimed at optimizing navigation as well as minimizing collision probabilities. A wide range of challenging settings such as static or dynamic environments were subjected to rigorous testing on the proposed system. The results indicate that it is robust and effective in detecting obstacles reliably to enhance navigation based on its capacity to make adjustments during operation time (discovered employing experimentation that took place in these settings). © 2024 IEEE.

关键词： image acquisition

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RGB-Guided Resolution Enhancement of IR images 30

RGB-Guided Resolution Enhancement of IR Images

引用

30th International conference on systems, Signals and image processing, IWSSIP 2023

作者： Trammer, Marcel Genser, Nils Seiler, Jurgen Ai & Signal Processing Lab Sielaff GmbH & Co. Kg Herrieden Germany Multimedia Communications and Signal Processing Erlangen Germany

ISBN: (纸本)9798350337297

This paper introduces a novel method for RGB-Guided Resolution Enhancement of infrared (IR) images called Guided IR Resolution Enhancement (GIRRE). In the area of single image super resolution (SISR) there exists a wide variety of algorithms like interpolation methods or neural networks to improve the spatial resolution of images. In contrast to SISR, even more information can be gathered on the recorded scene when using multiple cameras. In our setup, we are dealing with multi image super resolution, especially with stereo super resolution. We consider a color camera and an IR camera. Current IR sensors have a very low resolution compared to color sensors so that recent color sensors take up 100 times more pixels than IR sensors. To this end, GIRRE increases the spatial resolution of the low-resolution IR image. After that, the upscaled image is filtered with the aid of the high-resolution color image. We show that our method achieves an average PSNR gain of 1.2dB and at best up to 1.8 dB compared to state-of-the-art methods, which is visually noticeable. © 2023 IEEE.

关键词： image enhancement

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image Enhancement by Defogging utilizing Scene Specific Dark Channel Prior

Image Enhancement by Defogging utilizing Scene Specific Dark...

引用

2024 IEEE International Students' conference on Electrical, Electronics and Computer Science, SCEECS 2024

作者： Yadav, Agnesh Chandra Bose, Samprit Kolekar, Maheshkumar H. Iit Patna Dept. Electrical Engineering Bihar India

ISBN: (纸本)9798350348460

Adverse weather conditions such as haze and fog significantly impact the visibility and quality of outdoor images, leading to errors in various computer vision systems. Traditional defogging methods, often fall short in terms of efficiency and accuracy. In this study, an approach is presented to address these challenges. The presented method involves estimating the approximate depth map of a hazy image, from which the scene-specific dark channel and transmission are derived. Post-processing includes histogram normalization, further enhancing the overall image quality. By incorporating these steps, the technique aims to surpass the limitations of conventional defogging algorithms, offering improved efficiency and accuracy in restoring the quality of individual images affected by adverse weather conditions. The outcomes from the experiments demonstrated a noteworthy enhancement in both visible and quantitative aspects compared to other leading techniques. © 2024 IEEE.

关键词： Defogging image quality restore scene-specific dark channel

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Exploring the Efficacy of Spatial Subsampling Methods for 3D image Projection for 2D Classification

Exploring the Efficacy of Spatial Subsampling Methods for 3D...

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2024 IEEE International conference on Imaging systems and Techniques, IST 2024

作者： Wicaksono, Alif Aditya Purnama, I Ketut Eddy Rachmadi, Reza Fuad Muqtadiroh, Feby Artwodini Priyadi, Ardyono Purnomo, Mauridhi Hery Institut Teknologi Sepuluh Nopember Dept. of Electrical Engineering Surabaya Indonesia Institut Teknologi Sepuluh Nopember Dept. of Computer Engineering Surabaya Indonesia Institut Teknologi Sepuluh Nopember Dept. of Information Systems Surabaya Indonesia

ISBN: (纸本)9798350378214

In this paper we purpose several methods for creating 2D projection image from a 3D scan such as from CT or MR scans, and then look at different types of 2.5D projections with a growing window sizes and see its effects on the efficacy of the machine learning model when combined with the selection algorithms. As such we are using Shi-Tomasi Detectors, Sobel Edge Detectors, Sum of Pixel Intensity, Center Select, and Random Selection as selection algorithms from which we select the most interesting index for a given scan, from which depending on the window size, we stack the neighboring slices in the axial plane to the channel dimension creating a 2.5D image from which we could pass into our ResNet-9 model configured for classification and train the model for a given number of epochs, under the same conditions for all of our tests, this ensures that for all of our experiments the main effector is window size and the selection algorithm. From our tests we found that the Center Select on average outperforming the other selection algorithm, this result indicate that medical information is mostly centered around the scan, and when combined with the saving of 60% less parameters, the purposed method shows a new way of processing 3D Scans for processing with a 2D CNN model. © 2024 IEEE.

关键词： Convolutional neural networks

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Comprehensive Survey On Remote Sensing image processing Techniques for image Classification 12th

Comprehensive Survey On Remote Sensing Image Processing Tech...

引用

12th EAI International conference on Context-Aware systems and Applications, ICCASA 2023

作者： Tran, Thuy Thi Huynh, Hiep Xuan Faculty of Information Technology – Communication University of CuuLong Vinh Long Viet Nam College of Information and Communication Technology Can Tho University Can Tho Viet Nam

ISBN: (纸本)9783031588778

Remote sensing technology is now being used with unprecedented high resolution, making important contributions in practical applications such as urban development, construction planning and disaster prediction. However, although many scholars have studied algorithms for remote sensing image processing, there have not been detailed summary articles to support new researchers in this field. In this paper, we present an overview of remote sensing images, types of remote sensing satellite images and related studies. Next, we briefly review the recent history of remote sensing image processing techniques. Then, list related studies on remote sensing image classification. Finally, based on the current status of research on remote sensing images, we propose some future research directions in order to provide survey references for new studies in the field of remote sensing. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Urban planning

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Convergent Bregman Plug-and-Play image Restoration for Poisson Inverse Problems 37

Convergent Bregman Plug-and-Play Image Restoration for Poiss...

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37th conference on Neural Information processing systems (NeurIPS)

作者： Hurault, Samuel Kamilov, Ulugbek Leclaire, Arthur Papadakis, Nicolas Univ Bordeaux CNRS INRIA Bordeaux INPIMBUMR 5251 Bordeaux France Washington Univ St Louis MO 63110 USA Univ Bordeaux CNRS INRIA Bordeaux INPIMBUMR 5251LTCITelecom ParisIP P Bordeaux France

ISBN: (纸本)9781713899921

Plug-and-Play (PnP) methods are efficient iterative algorithms for solving ill-posed image inverse problems. PnP methods are obtained by using deep Gaussian denoisers instead of the proximal operator or the gradient-descent step within proximal algorithms. Current PnP schemes rely on data-fidelity terms that have either Lipschitz gradients or closed-form proximal operators, which is not applicable to Poisson inverse problems. Based on the observation that the Gaussian noise is not the adequate noise model in this setting, we propose to generalize PnP using the Bregman Proximal Gradient (BPG) method. BPG replaces the Euclidean distance with a Bregman divergence that can better capture the smoothness properties of the problem. We introduce the Bregman Score Denoiser specifically parametrized and trained for the new Bregman geometry and prove that it corresponds to the proximal operator of a nonconvex potential. We propose two PnP algorithms based on the Bregman Score Denoiser for solving Poisson inverse problems. Extending the convergence results of BPG in the nonconvex settings, we show that the proposed methods converge, targeting stationary points of an explicit global functional. Experimental evaluations conducted on various Poisson inverse problems validate the convergence results and showcase effective restoration performance.

关键词： Inverse problems

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NIS3D: A Completely Annotated Benchmark for Dense 3D Nuclei image Segmentation 37

NIS3D: A Completely Annotated Benchmark for Dense 3D Nuclei ...

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37th conference on Neural Information processing systems (NeurIPS)

作者： Zheng, Wei Peng, James Cheng Hou, Zeyuan Lyu, Boyu Wang, Mengfan Mi, Xuelong Qiao, Shuoxuan Wan, Yinan Yu, Guoqiang Virginia Tech Dept Elect & Comp Engn Blacksburg VA 24061 USA Univ Basel Biozentrum Basel Switzerland

ISBN: (纸本)9781713899921

3D segmentation of nuclei images is a fundamental task for many biological studies. Despite the rapid advances of large-volume 3D imaging acquisition methods and the emergence of sophisticated algorithms to segment the nuclei in recent years, a benchmark with all cells completely annotated is still missing, making it hard to accurately assess and further improve the performance of the algorithms. The existing nuclei segmentation benchmarks either worked on 2D only or annotated a small number of 3D cells, perhaps due to the high cost of 3D annotation for large-scale data. To fulfill the critical need, we constructed NIS3D, a 3D, high cell density, large-volume, and completely annotated Nuclei image Segmentation benchmark, assisted by our newly designed semi-automatic annotation software. NIS3D provides more than 22,000 cells across multiple most-used species in this area. Each cell is labeled by three independent annotators, so we can measure the variability of each annotation. A confidence score is computed for each cell, allowing more nuanced testing and performance comparison. A comprehensive review on the methods of segmenting 3D dense nuclei was conducted. The benchmark was used to evaluate the performance of several selected state-of-the-art segmentation algorithms. The best of current methods is still far away from human-level accuracy, corroborating the necessity of generating such a benchmark. The testing results also demonstrated the strength and weakness of each method and pointed out the directions of further methodological development. The dataset can be downloaded here https://***/yu-lab-vt/NIS3D.

关键词： Cells

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