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

共 16347 条记录，以下是511-520 订阅

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A fast hand-eye calibration method 2

A fast hand-eye calibration method

引用

2nd International conference on Advanced algorithms and Signal image processing, AASIP 2022

作者： Luo, Hua Zhang, Ke Shang, Junyun Zhang, Lili Yang, Na Guo, Jing Northwestern Polytechnical University Xi'an710072 China Xi'an Aerospace Times Precision Mechatronics Company Limited Xi'an710100 China

ISBN: (纸本)9781510660571

The traditional hand-eye calibration needs to take the calibration target image acquired by the vision system and the corresponding robot pose information as input, the process is complicated, and there is a risk of calibration failure when the data are not corresponding. To solve these problems, a fast hand-eye calibration method is proposed. According to the principle that a certain point in space has the same three-dimensional(3D) coordinates in its coordinate system after the motion of the coordinate system, to control the end of the robot to carry out multiple translation and rotational motion, the traditional hand-eye calibration model AX=XB is simplified into AX=B. The hand-eye calibration matrix can be quickly solved only by the transformation between the camera coordinate system and the calibration target coordinate system. The experimental results show that the proposed method is simple, fast and high accuracy. It can be applied to eye-in-hand system and eye-to-hand system. © 2022 SPIE.

关键词： Robots

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Parallel Dual Broad Learning Surrogate Assisted Semi-supervised Kernel Multi-objective Evolutionary Rough Fuzzy Clustering Algorithm for image Segmentation

Parallel Dual Broad Learning Surrogate Assisted Semi-supervi...

引用

Natural Language processing (ICNLP), International conference on

作者： Weilin Du Feng Zhao School of Communications and Information Engineering (School of Artificial Intelligence) Xi’an University of Posts and Telecommunications Xi’an China

ISBN: (数字)9798350349115

ISBN: (纸本)9798350349122

To improve the segmentation performance of multi-objective evolutionary clustering algorithms, this paper proposes a parallel dual broad learning surrogate assisted semi-supervised kernel multi-objective evolutionary rough fuzzy clustering algorithm (PDBLS-SKMRFC) for image segmentation. First, the algorithm constructs a parallel dual broad learning surrogate assisted multi-objective evolutionary framework. It uses two broad learning systems as classification and regression surrogate models to evaluate the population in parallel manner. In the framework, a multi-population division strategy guided by dual broad learning system, a dominant individual crossover strategy, a sub-population mutation strategy, and a hierarchical environment selection strategy are designed to obtain more excellent offspring populations. Then, a semi-supervised kernel rough fuzzy intra-class compactness function is constructed, which uses a few labels and pseudo-labels as supervision information to improve the image segmentation performance, and evaluates the clustering quality together with the kernel separability function. Finally, a semi-supervised kernel rough fuzzy clustering validity index is designed to select the optimal solution from the final non-dominated solution set for image segmentation. Experimental results on color images show the effectiveness of the proposed algorithm.

关键词： Learning systems image segmentation Clustering algorithms Color Linear programming Natural language processing Classification algorithms Indexes Kernel Standards

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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...

引用

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...

引用

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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image Encryption Algorithm Based on Combination Chaotic System and DNA Coding 4

Image Encryption Algorithm Based on Combination Chaotic Syst...

引用

4th International conference on Natural Language processing, ICNLP 2022

作者： Mao, Panpan Zhang, Xuefeng Jiang, Wen Xi'an University of Posts and Telecommunications School of Cyberspace Security Xi'an710121 China National Internet Emergency Center Beijing100029 China

ISBN: (数字)9781665495448

ISBN: (纸本)9781665495448

In order to increase the chaotic parameter range, improve the initial sensitivity of the chaotic system and the security of the image encryption algorithm, This paper proposed a new image encryption based on combination chaotic system and DNA coding. Two one-dimensional chaotic maps are nested to obtain a combined chaotic system, and the chaotic sequences generated by the combined chaotic system is amplified and modulated to obtain the DNA coding rule sequences and the scrambling sequences, and the uniformity of the coding rules are improved through rule replacement operation. Using DNA encoding, DNA exclusive-or(XOR),and DNA decoding operations to achieve plain image diffusion, bit-level permutation is performed on the diffused image through the permutation sequences to obtain encrypted image. Theoretical and experimental simulation analysis shows that the chaotic interval of the combined chaotic system is increased and the initial value sensitivity is improved. The encryption algorithm based on the combined chaotic system and DNA coding can effectively resist statistical attacks, differential attacks and exhaustive attacks, the security of the encryption algorithm is also significantly improved compared to other algorithms. © 2022 IEEE.

关键词： Chaotic systems

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Shadow Removal from a Single image Using an Enhanced Generative Adversarial Network 19

Shadow Removal from a Single Image Using an Enhanced Generat...

引用

19th International conference on Natural Computation, Fuzzy systems and Knowledge Discovery, ICNC-FSKD 2023

作者： Zhang, Jing Kong, Weiwei Xi'an University of Posts and Telecommunications College of Computer Science Xi'an China Xi'an University of Posts and Telecommunications The Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi'an China

ISBN: (纸本)9798350304398

image shadow removal is challenging due to the diversity of shadows and the dependence on the background of the area covered by shadows. In this paper, we design an enhanced generative adversarial network (EGAN) to handle the shadow removal task. EGAN is a complicated generative adversarial network that may exploit previous info, like shadow masks and lightness estimation, for improving recovery capability. In addition, EGAN can effectively utilize the details of shadow regions and eliminate artifacts. EGAN owns three main advantages. First, EGAN employs stricter rules for discriminators, which can upgrade the instability of traditional GAN. Second, EGAN involves a completely unique enhanced attention module, which may efficiently pick up different types of previous info to accelerate the learning efficiency of image reconstruction. Finally, EGAN is essentially an original cascaded network, that is, DRDU, which is beneficial for efficiently detecting hierarchical features of image recovery. Simulation experiments are conducted to verify the effectiveness of the proposed method on two benchmark datasets including SRD and ISTD, the strengths of our proposed method are indicated over the current representative ones according to subjective performance and objective estimation indexes. © 2023 IEEE.

关键词： image reconstruction

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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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