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Enhancing image Segmentation through an Innovative Hybrid Kernel: A Weighted Fusion of Sobel and Prewitt Operators Using Artificial Neural Networks 1

Enhancing Image Segmentation through an Innovative Hybrid Ke...

引用

1st international conference on Computing, Sciences and Communications, ICCSC 2024

作者： Verma, Ankush Dhanda, Namrata Yadav, Vibhash Amity Institute of Information Technology Amity University Uttar Pradesh Department of Information Technology Lucknow India Amity School of Engineering and Technology Amity University Uttar Pradesh Department of Computer Science & Engineering Lucknow India Rajkiya Engineering College Department of Information Technology Banda India

ISBN: (纸本)9798350353648

image segmentation, a pivotal element in computer vision, relies on effective edge detection to delineate boundaries within images. Traditional methods, including Canny, Sobel, Prewitt, and Laplacian, while widely used, may exhibit limitations that necessitate pre- and post-processing techniques for optimal results. In response to this, our paper introduces an innovative hybrid kernel, constructed from the weighted average of Sobel and Prewitt operators, with weights determined through an Artificial Neural Network (ANN). The objective is to synergize the strengths of these operators, enhancing the precision of edge detection. The proposed hybrid kernel is rigorously evaluated against established techniques, such as Sobel and Canny, utilizing comprehensive metrics like Peak signal-to-Noise Ratio (PSNR) and F-score. Results consistently demonstrate that the hybrid kernel outperforms previously published outcomes, showcasing notable improvements in edge detection quality and accuracy. This research positions the hybrid kernel approach as a promising alternative for image segmentation, offering advancements beyond conventional methods. © 2024 ieee.

关键词： image segmentation

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A Power-Efficient, Analog Integrated, Sigmoid-Based Edge Detector

A Power-Efficient, Analog Integrated, Sigmoid-Based Edge Det...

引用

2024 international conference on Microelectronics, ICM 2024

作者： Alimisis, Vassilis Dimas, Christos Sotiriadis, Paul P. National Technical University of Athens Department of Electrical and Computer Engineering Greece and Archimedes/Athena RC Athens15780 Greece

ISBN: (纸本)9798350379396

Edge detection is a powerful tool widely employed in numerous Computer Vision applications. One of its key functions is to identify and define the spatial boundaries of objects within an image, allowing for the segmentation and recognition of these objects. Like many Computer Vision techniques, edge detection is computationally intensive, but it lends itself well to parallel processing. As a result, hardware-specific implementations offer significant advantages over traditional CPU-based methods, providing faster and more efficient processing. In this paper, we introduce a hardware-optimized version of the Robert Cross operator based on sigmoid function circuit. This design, along with its building blocks, achieves notable efficiency in both power and area consumption. This circuit was tested on specific images, attaining a medium Structural Similarity Index Metric of 0.83, with each pixel requiring only 820μ m2 of chip area. The proposed edge detector was implemented and verified employing a TSMC 90nm CMOS process, with the tool Cadence IC Suite. © 2024 ieee.

关键词： image segmentation

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Ambulance Detection in Traffic signals Using image processing 5

Ambulance Detection in Traffic Signals Using Image Processin...

引用

5th international conference on Inventive Research in Computing applications, ICIRCA 2023

作者： Sanjai, P.C. Sam, Jebastin J. Iyengar, Shashank Kalimuthu, K. Srm Institute of Science and Technology Department of Ece Chennai India

ISBN: (纸本)9798350321425

Emergency vehicle classification is a system used to categorize vehicles used by emergency services based on their purpose and capabilities. This system typically divides emergency vehicles into several categories, such as ambulances, fire trucks, police cars, and others. This research study categorizes ambulances using various machine learning techniques. Emergency vehicle classification of ambulances is extremely crucial for ensuring efficient emergency response and instant effect. © 2023 ieee.

关键词： Ambulances

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Design and Implementation of High-Performance Multi-Level Approximate Multiplier 2

Design and Implementation of High-Performance Multi-Level Ap...

引用

2nd international conference on Distributed Computing and Optimization Techniques, ICDCOT 2024

作者： Karukumalli, Naga Sai Kumar, Satish Hegde, Ganapathi Amrita School of Engineering Dept. Electronics and Communication Bangalore India

ISBN: (纸本)9798350382952

In computers and digital electronics, digital multiplication is a fundamental mathematical operation. Because multiplier applications are inherently error-tolerant, approximate multipliers are created. Approximate multipliers are primarily designed to accomplish a compromise between precision and enhanced performance factors like speed, power efficiency, and efficient use of chip area in digital circuit designs. They aim to deliver results that closely approximate the exact multiplication outcome while bringing significant benefits to a wide range of applications. In this study, we present a novel 4-2 approximation compressor architecture that makes use of multiplexers. This is achieved by replacing portions of the normal AND/OR gates with approximate MUX-based logic. The various high-speed 5-3, 10-4, 15-4, and 20-5 compressors are being developed using MUX-based logic. Utilizing the 5-3,10-4, 15-4, and 20-5 compressor structures, the multiplier's partial products are combined. The circuits under investigation are used to create 8 × 8 multipliers, 16 × 16 multipliers, 32 × 32 multipliers, and 64 × 64 multipliers implemented in CMOS 45nm technology. The suggested compressor achieves an 11.9% reduction in delay when compared to the precise compressor and the suggested multiplier achieves a 39% reduction in delay Consequently, this design is well-suited for applications demanding increased processing speed. © 2024 ieee.

关键词： image processing

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QRFPose: Query-Based 3D Pose Estimation using Radio signals 16

QRFPose: Query-Based 3D Pose Estimation using Radio Signals

引用

16th international conference on Wireless Communications and signal processing, WCSP 2024

作者： Wan, Hong Song, Ruiyuan Xie, Chunyang Lu, Zhi Chen, Qi Wu, Zhi Zhang, Dongheng Hu, Yang Chen, Yan School of Cyber Science and Technology University of Science and Technology of China Hefei China Qianyuan National Laboratory Hangzhou China School of Information Science and Technology University of Science and Technology of China Hefei China

ISBN: (纸本)9798350390643

The major challenge for radio-frequency-based (RF) multi-person pose estimation is to solve the problem of the global information-sparsity and local information-dense in RF signals. Unlike the visual image that the human body is located in a determined region, the majority of information regarding the human body in RF signals is concentrated in localized areas, with a small portion dispersed across global regions. However, the existing works directly follow the divide-and-conquer strategy to detect candidate regions where people may exist, and then zoom into each local region to generate human skeletons, while the information beyond local information-dense regions is ignored resulting in performance degradation. To resolve the problem, we propose a novel query-based multi-person pose estimation framework, QRFPose, to view body joints as learnable query embeddings to adaptively focus on features related to target skeleton joints. Moreover, QRFPose is carefully designed to take the geometric prior of horizontal and vertical RF signals into consideration. By leveraging the projective deformable attention rather than the naive global attention mechanism, QRFPose works more efficiently. The experimental results show that QRFPose plays favorably against state-of-the-art approaches in terms of both accuracy and efficiency. © 2024 ieee.

关键词： image segmentation

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Graphene Based Dual Port Octagonal Three Element Series Feed Array Antenna for Terahertz applications 9

Graphene Based Dual Port Octagonal Three Element Series Feed...

引用

9th international conference on Wireless Communications, signal processing and Networking, WiSPNET 2024

作者： Pandey, Govind Kumar Rama Rao, T. SRM Institute of Science and Technology Dept. of Electronics and Communications Engineering Tamilnadu Kattankulathur603203 India

ISBN: (纸本)9798350350845

This paper presents, a Graphene-based octagonal three-element series feed (OTESF) array antenna designed for terahertz (THz) communication at short distances. The OTESF array antenna comprises four layers, utilizing gold for both ground and patch. The substrate consists of quartz (SiO4) with a thickness of 140 μm and a 10 nm thick graphene layer is incorporated after the patch layer in this array antenna design. The unit cell of the OTESF array antenna exhibits excellent performance, showcasing a reflection coefficient below-10 dB within the 0.285 to 0.535 THz frequency range. This achievement corresponds to a significant bandwidth of 250 GHz. additionally, the peak realized gain is measured at 5.25 dBi, making the OTESF array antenna a highly promising candidate for applications in Multiple Input Multiple Output (MIMO) setups. In dual Port (DP) mode configurations (1×2 MIMO), where the OTESF array antenna elements are organized orthogonally. The DP MIMO antenna features a cross-sectional area with dimensions of 1225.71 μm × 2155.71 μm. The designed MIMO array attains a bandwidth of 0.256 THz, operating in the frequency ranges from 0.286 to 0.542 THz and realized gain of 7.5 dBi, and the isolation loss is consistently kept below-20 dB. © 2024 ieee.

关键词： Graphene

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A Noise-robust Locality Transformer for Fine-grained Food image Retrieval 5

A Noise-robust Locality Transformer for Fine-grained Food Im...

引用

ieee 5th international conference on Multimedia Information processing and Retrieval (MIPR)

作者： Song, Jiajun Min, Weiqing Liu, Yuxin Li, Zhuo Jiang, Shuqiang Rui, Yong Chinese Acad Sci Key Lab Intell Info Proc Inst Comput Tech Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Lenovo Grp Beijing Peoples R China

ISBN: (数字)9781665495486

ISBN: (纸本)9781665495486

Food image retrieval has wide applications in the multimedia community. However, there are two main challenges for food image retrieval. First, food images are often disturbed by food-irrelevant information such as plates and side dishes. Second, fine-grained characteristics of food images make visual representation of different categories similar. To solve them, we propose the Noiserobust Locality Transformer (NoLoTransformer) for food image retrieval under the metric learning-based retrieval framework. Specifically, we propose two novel modules, named Patch Attention Module (PAM) and Local Perception Unit (LPU) for the Transformer-based feature extraction. PAM weakens the negative impact of the noise in the food image by reweighting different patches and distributing low weights to noisy patches adaptively. LPU extracts local features by introducing convolution and then obtains the fine-grained information in the local feature. Extensive evaluation on three datasets demonstrates the effectiveness of the proposed method. Code is available at https:// ***/ Jiajun- ISIA/ NoLoTransformer

关键词： Learning systems Visualization Convolution image retrieval Information processing Feature extraction Transformers

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applications and Limits of image-to-image Translation Models 24

Applications and Limits of Image-to-Image Translation Models

引用

24th international conference on Digital signal processing, DSP 2023

作者： Coscia, Pasquale Genovese, Angelo Scotti, Fabio Piuri, Vincenzo Department of Computer Science Università degli Studi di Milano Italy

ISBN: (纸本)9798350339598

image-to-image (I2I) translation models are widely employed in several fields, e.g., computer vision, security or medicine. Their goal is to map images from a source domain to a target domain while preserving content information. Despite their success, these models suffer from multiple weaknesses. For example, many practical scenarios do not consent to collect a sufficient amount of images, leading to imbalanced domains. Furthermore, mode collapse and training instability require a careful design and further discourage their deployment on edge devices. Finally, I2I models need an intensive computation to learn conditional probability distributions and are difficult to adapt to different contexts. These drawbacks mainly limit their large scale applicability. In this work, we want to shed light on the main solutions adopted to overcome the above issues and their impact on the performance. We also investigate several approaches to deploy these models on low-powered devices and weight sharing techniques to reduce the number of parameters and resources used. © 2023 ieee.

关键词： Probability distributions

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A ROBUST OBJECT SEGMENTATION NETWORK FOR UNDERWATER SCENES 47

A ROBUST OBJECT SEGMENTATION NETWORK FOR UNDERWATER SCENES

引用

47th ieee international conference on Acoustics, Speech and signal processing (ICASSP)

作者： Chen, Ruizhe Fu, Zhenqi Huang, Yue Cheng, En Ding, Xinghao Xiamen Univ Key Lab Underwater Acoust Commun & Marine Informa Minist Educ Xiamen Peoples R China Xiamen Univ Sch Informat Xiamen Peoples R China Xiamen Univ Inst Artificial Intelligence Xiamen Peoples R China

ISBN: (纸本)9781665405409

Underwater object segmentation is one of the key technologies in the fields of marine biology research and autonomous underwater vehicles. The challenges of underwater object segmentation originate from two aspects, 1) the complex underwater environment and 2) the camouflage characteristics of marine animals. In this paper, we propose WaterSNet, an underwater object segmentation network to address these challenges. Specified, we propose a random style adaption (RSA) module as well as a siamese structure to reduce the impact of water degradation diversity. We also extract multiscale features via the receptive field block (RFB) module, and then fuses multi-level features to better utilize global context information via the attention fusion block (AFB) module. Experimental results on marine animal dataset MAS3K demonstrate that the proposed method outperforms other state-ofthe-art methods significantly.

关键词： underwater image image segmentation camouflaged objects attention feature fusion

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image Segmentation on Gabor Filtered images using Projective Transformation

Image Segmentation on Gabor Filtered images using Projective...

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2023 ieee international conference on Recent Trends in Electronics and Communication, ICRTEC 2023

作者： Gupta, Shashi Kant Alemran, Ahmed Singh, Prabhdeep Khang, Alex Dixit, Chandra Kumar Haralayya, Bhadrappa Eudoxia Research University Department of Cse United States Medicine College-Misan University Physics Department Al Amarah00964 Iraq School of Computer Applications Bbd University UP Lucknow India University of Science and Technology Department of Information Technology United States Dr. Shakuntala Misra National Rehabilitation University Department of Physics UP Lucknow226017 India Lingaraj Appa Engineering College Bidar Department of Mba Karanataka Bidar585403 India

ISBN: (纸本)9798350396195

In recent years, image segmentation has been applied on various images for obtaining various results. They are being deployed in numerous applications. There are lot of techniques adopted to make the image distortion free. Methods are also applied when the original image needs to be extracted from the image containing the background. Projective transformation is one of the techniques where we can apply phase correlation among the images and segment the part of the image that is needed for the next processing step. In this proposed work, we have deployed a model where an input image is given. The image is then undergone into various scaling techniques. Use of active contours and graph cut methods are embedded to obtain the segmented image. The key role of this model is to apply the Gabor filters and perform projective transformation among the image to segment the original part of the image from its background. The results are proposed by giving an output in a binary form. The work runs for a maximum of 100 iterations and for that the relaxation factor is taken as 0.5. © 2023 ieee.

关键词： Gabor filters

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