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

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AI-based Gender Identification using Facial Features 2

AI-based Gender Identification using Facial Features

引用

2nd International conference on Applied Artificial Intelligence and Computing, ICAAIC 2023

作者： Venkateswarlu, B. Sunanda, N. Kumar, A Yaswanth Mani Reddy, A Naga Siva Charan Hyndav, B. Ram Gopal Koneru Lakshmaiah Education Foundation Department of Cse Guntur India Vnr Vignana Jyothi Institute of Engineering & Technology Department of CSE-DS CYS Ai&ds Hyderabad India

ISBN: (纸本)9781665456302

The identification of gender through facial images has gained significant importance in recent times. In the domain of human recognition through image processing, biometric features like facial structure, iris, voice, and other physical characteristics are employed to establish unique identification of individuals. As the quantity of image data on the internet continues to rise, the need for Artificial Intelligence (AI) algorithms capable of performing classification tasks like face and gender recognition has grown exponentially. With the increasing prevalence of machine-to-machine interaction, and the emphasis on ethical, efficient, and individual-centric systems becoming more pronounced, gender identification software has become an increasingly popular tool. Automated gender identification software has gained popularity in the era of exchange of information between two or more machines. The method for detecting the face involves using the Haar Cascade face detection technique, which employs the Viola-Jones face recognition algorithm. After detecting the face, the eyes, mouth, and nose can be identified as facial features using various computer vision techniques. Adaptive filters are utilized to decrease noise prior to detection process in order to increase gender identification accuracy. The gathered facial characteristics serve the neural network as input or test data, which is then trained on these features. The neural network is designed to learn gender-specific features and operate as a classifier for gender detection. © 2023 IEEE.

关键词： image enhancement

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Comparison of image Feature Detection algorithms 9

Comparison of Image Feature Detection Algorithms

引用

9th International conference on Dependable systems and Their Applications, DSA 2022

作者： Xu, Fan Liu, Xia Cui, Yanli Yan, Mingdie Lai, Zhongyuan Intelligent Manufacturing of JianghanUniversity Hubei Wuhan China Artificial Intelligence of JianghanUniversity Hubei Wuhan China

ISBN: (数字)9781665488778

ISBN: (纸本)9781665488778

The key of image processing is to extract feature points and feature vectors by appropriate methods. In order to analyze the application effect of common feature extraction methods in different scenarios, this paper adopts SIFT, BRISK, ORB, KAZE and AKAZE methods to rotate, adjust brightness, blur and zoom images based on two data sets. The operating efficiency, the ratio of feature points before and after operation, the best matching rate and accuracy rate of feature points pair of the five methods are analyzed, and the suggestions for selecting reasonable feature detection methods for different application scenarios are given. © 2022 IEEE.

关键词： Feature extraction

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Sign Language Translation Using image processing to Audio Conversion

Sign Language Translation Using Image Processing to Audio Co...

引用

IEEE International conference on Intelligent Techniques in Control, Optimization and Signal processing (INCOS)

作者： V Subashini B Someshwaran S Sowmya S Ashwin Kumar Department of Electronics and Communication Engineering Rajalakshmi Institute of Technology Chennai India

ISBN: (数字)9798350361186

ISBN: (纸本)9798350361193

Sign language has long been a fundamental mode of communication for deaf and mute individuals, serving as a crucial tool for inclusivity and interaction. Nonetheless, communication barriers persist as many individuals outside of these communities struggle to comprehend and utilize sign language effectively. A ground-breaking system known as hand gesture recognition using image processing to audio conversion has emerged to address this issue. This innovative system aims to develop an application capable of translating sign language and hand gestures into text and audio, thereby facilitating communication between deaf and mute individuals and the wider society. This system enables the detection and classification of hand gestures by employing computer vision techniques, such as CNN algorithms for image processing and the MediaPipe framework for hand gesture identification in real-time video streams. Subsequently, the system utilizes audio signals to provide immediate feedback by converting the detected gestures into corresponding sounds. The feature extraction CNN algorithm is implemented in Python, while the execution takes place on a Raspberry Pi connected to an external camera utilizing OpenCV libraries. Through this comprehensive approach, the system endeavours to bridge the communication gap and enhance the inclusion of deaf and mute individuals in various social settings.

关键词： Sign language image recognition Signal processing algorithms Streaming media Signal processing Libraries Real-time systems

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Through-the-Wall Synthetic Aperture Radar Imaging Using 2-D Spectral Estimation Methods

Through-the-Wall Synthetic Aperture Radar Imaging Using 2-D ...

引用

2022 Innovations in Intelligent systems and Applications conference, ASYU 2022

作者： Dasbasi, Melek Hocaoglu, A. Koksal Savunma Teknolojileri Enstitüsü Gebze Teknik Üniversitesi Kocaeli Turkey Elektronik Mühendisliǧi Gebze Teknik Üniversitesi Kocaeli Turkey

ISBN: (数字)9781665488945

ISBN: (纸本)9781665488945

In this study, adaptive signal processing algorithms are investigated to obtain high-resolution radar images of concealed targets. For this purpose, a vector network analyzer is used as a stepped frequency continuous wave-based radar system, and B-scan radar data is collected from concealed targets. synthetic aperture radar algorithm is applied to raw data to improve the azimuth resolution. Then, 2D Capon and MUSIC spectral estimation methods are implemented to the data obtained by the synthetic aperture radar algorithm for through-the-wall imaging applications. Fusion of synthetic aperture radar and spectral estimation methods are represented to compare enhanced image quality for better target detection. © 2022 IEEE.

关键词： image enhancement

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Research on Smoke image Recognition: Multi-Scale Dilated Convolutional Neural Network and Entropy Function Threshold

Research on Smoke Image Recognition: Multi-Scale Dilated Con...

引用

Signal processing, Communications and Engineering Management conference (ISPCEM), International

作者： Yongmei Xiao Xing Wang Officers College of PAP Chengdu China

ISBN: (数字)9798331528676

ISBN: (纸本)9798331528683

For the application of artificial intelligence in image-based smoke detection in emergency management, this paper proposes an image recognition algorithm based on a multi-scale dilated convolutional neural network and entropy threshold function to prevent the loss of small-scale features, low detection rate, and poor real-time performance of smoke image recognition. First, the smoke features are determined according to a multi-scale analysis model, and multi-scale information such as texture, color, and shape of the smoke image is obtained. Second, we propose a dilated convolutional neural network to solve the feature loss. Third, according to the characteristics of the entropy function, we build a model that comprehensively considers smoke features and recognition thresholds, which more accurately describes the image recognition process. Ultimately, this research develops a smoke detection system using the suggested algorithm and demonstrates its efficacy through simulation and experimental validation.

关键词： image recognition Shape image color analysis Engineering management Signal processing algorithms Signal processing Feature extraction Entropy Real-time systems Convolutional neural networks

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Automated Dengue Recognition and Analysis through image processing and Machine Learning

Automated Dengue Recognition and Analysis through Image Proc...

引用

Integrated Circuits and Communication systems (ICICACS), IEEE International conference on

作者： Preethi N Patil Usha J Andhe Dharani Department of MCA RV College of Engineering Bangalore India

Detecting dengue fever using image processing techniques typically involves the analysis of medical images such as blood smears or tissue samples. Dengue is a viral disease transmitted by Aedes mosquitoes, and its diagnosis primarily relies on clinical symptoms, serological tests, and molecular assays. image processing can be used as a complementary tool to assist and identify the dengue virus or related disparities in the body. Dengue fever, alternatively known as break-bone fever, is a lifethreatening arboviral disease caused by the DENV virus. It is a major global health concern with an increasing incidence worldwide. The existing clinical methods for diagnosing dengue are manual, requiring significant time and labor. The present work aims to develop an automated system using machine learning and digital image analysis to detect dengue infection from blood smear images. The custom algorithms are designed to extract platelets, red blood cells, and white blood cells, and train a feature vector. By automating the analysis of blood smear images, aids healthcare professionals detect cases of dengue more efficiently, allowing for early treatment and potentially saving lives. However, it is crucial to address data quality, algorithm selection, validation, interpretability, and ethical considerations throughout the development process.

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Algorithm of Palm Vein image Selection for Biometric Authentication systems Based on Multidimensional Markov Chain

Algorithm of Palm Vein Image Selection for Biometric Authent...

引用

Digital Signal processing and its Applications (DSPA), International conference on

作者： Natalya Kharina Anton Zemtsov Sergei Chernyadyev Department of the Radio Electronic Means Vyatka State University Kirov Russia Institute of Mathematics and Information Systems Vyatka State University Kirov Russia

Biometric palm vein authentication becomes more popular in the industry. This paper proposes an algorithm for palm vein image selection. The main idea of this method is an approximation of biometric template image through discrete Markov process and applying the theory of conditional Markov process to develop the algorithm, which allows to fully utilize the statistic redundancy of the biometric template. Given method can be effectively used after performing a thresholding process on an image, using the dynamic threshold value. CASIA MS Palmprint V1 Database dataset was used to present the examples of algorithm implementation. Morphological dilation and Zhang-Suen algorithms were used to evaluate and compare the effectiveness of the proposed palm vein image thinning algorithm. The results showed that the proposed method makes it possible to compute an image that preserves the vein thickness and closely matches the real vein pattern and is effective when using a template matching algorithm based on perceptual hash functions.

关键词： Thresholding (Imaging) Biometrics (access control) Veins Heuristic algorithms Redundancy Signal processing algorithms Authentication

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Relative Gradient Matching Cost for Mitigating Feature Discrepancies in Stereo Matching 5

Relative Gradient Matching Cost for Mitigating Feature Discr...

引用

5th International conference on High Performance Big Data and Intelligent systems, HDIS 2023

作者： Liu, Changlin Zhang, Yuan Sun, Linjun Zhang, Kaijie Cao, Bing Li, Zhiwei School of Semiconductor Science and Technology South China Normal University Guangzhou China School of Information Science and Technology Beijing Forestry University Beijing China AnnLab Institute of Semiconductors Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350394160

In stereo matching, perspective differences in images can cause feature inconsistencies. Traditional stereo matching algorithms compare pixel disparities using local parallel windows transformed by matching costs. However, this method under the fronto-parallel windows assumption may produce incorrect matching results when there are perspective differences in the feature scale. To address this issue, we propose a new cost computation method called relative gradient matching cost (RGC). RGC effectively handles feature perspective differences by robustly constraining feature matching relationships across varying object surface depths, simulating the effect of slanted support windows. We propose different improvement strategies for common traditional methods and DNN-based methods combined with RGC. In experiments, we compare the performance of RGC with some SOTA models. The experiment results demonstrate that RGC significantly improves the accuracy and stability of stereo matching, especially in cases with edge and discontinuity areas. ©2023 IEEE.

关键词： Stereo image processing

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Optimal Digital Algorithm of a Cognitive Synthetic Aperture Radar Operation 12

Optimal Digital Algorithm of a Cognitive Synthetic Aperture ...

引用

12th IEEE International Scientific Technical conference on Dependable systems, Services and Technologies (DESSERT) - Dependable and Trustworthy AI, IoE, Big Data Analytics for a Safe and Secure World

作者： Zhyla, Semen Volosyuk, Valeriy Pavlikov, Vladimir Vlasenko, Dmytro Mazurenko, Oleksandr Lisohorskyi, Bohdan Natl Aerosp Univ Aerosp Radioelect Syst Dept Kharkiv Aviat Inst Kharkiv Ukraine Kharkiv Natl Air Force Univ Chief Marshal Aviat I Fac Radiotech Air Def Forces Kharkiv Ukraine

ISBN: (纸本)9798350333046

The problem of optimal estimation of the complex scattering coefficient of the underlying surface in a digital radar with cognitive signal processing is considered. It is shown that it is possible to develop new algorithms not only in a heuristic way by combining together all the necessary structural components of a cognitive radar. To test the new approach the formation of an optimization problem for the synthesis of the optimal algorithm for the secondary filtering of the radar image of the surface was performed, and a solution was given. On the one hand the obtained algorithm corresponds to the operation of the extended Kalman-Bucy filter, and on the other hand, it has implementation features specifically for the task of terrain radar imaging. Based on the results of the analysis of the obtained expressions a structural diagram of the cognitive radar was synthesized.

关键词： cognitive radars optimal signal processing secondary processing adaptive receiver

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A Hybrid Density-Based Clustering Pipeline for Track Reconstruction

A Hybrid Density-Based Clustering Pipeline for Track Reconst...

引用

image processing, Computer Vision and Machine Learning (ICICML), International conference on

作者： Bijia You Zhiyun Xia School of Computer Science Beijing University of Posts and Telecommunications Beijing China School of Cyberspace Security Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350355413

ISBN: (纸本)9798350355420

In high-energy physics, the capability to accurately and efficiently track charged particles is essential for effective data analysis. This article introduces an innovative density-based clustering pipeline intended for the track reconstruction task, incorporating Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm and Ordering Points To Identify the Clustering Structure (OPTICS) algorithm. Results on simulated data suggest that the proposed method offers improvements in both effectiveness and robustness compared to traditional techniques, with performance on par with state-of-the-art neural network-based approaches. Furthermore, this pipeline demonstrates significant potential for real-time applications in high-energy physics experiments, offering a scalable and robust solution.

关键词： Machine learning algorithms Pipelines Noise Clustering algorithms Optics Robustness Real-time systems Pattern recognition Trajectory image reconstruction

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