Eurasip Journal on Image and Video Processing最新文献_第8页

A novel secured Euclidean space points algorithm for blind spatial image watermarking 一种新的空间图像盲水印安全欧几里德空间点算法

IF 2.4 4区计算机科学

Eurasip Journal on Image and Video Processing Pub Date : 2021-08-10 DOI: 10.1186/s13640-022-00590-w

Shaik Hedayath Basha, J. B

引用次数: 1

Superresolution reconstruction method for ancient murals based on the stable enhanced generative adversarial network 基于稳定增强生成对抗性网络的古壁画超分辨率重建方法

IF 2.4 4区计算机科学

Eurasip Journal on Image and Video Processing Pub Date : 2021-07-30 DOI: 10.1186/s13640-021-00569-z

Jianfang Cao, Yiming Jia, Minmin Yan, Xiaodong Tian

引用次数: 1

Trademark infringement recognition assistance system based on human visual Gestalt psychology and trademark design 基于人类视觉格式塔心理与商标设计的商标侵权识别辅助系统

IF 2.4 4区计算机科学

Eurasip Journal on Image and Video Processing Pub Date : 2021-07-22 DOI: 10.1186/s13640-021-00566-2

Kuo-Ming Hung, Li-Ming Chen, Ting-Wen Chen

引用次数: 0

Pansharpening based on convolutional autoencoder and multi-scale guided filter 基于卷积自动编码器和多尺度引导滤波器的泛锐化

IF 2.4 4区计算机科学

Eurasip Journal on Image and Video Processing Pub Date : 2021-07-19 DOI: 10.1186/s13640-021-00565-3

Ahmad AL Smadi, Shuyuan Yang, Zhang Kai, Atif Mehmood, Min Wang, Ala Alsanabani

引用次数: 4

Robust hand gesture recognition using multiple shape-oriented visual cues 鲁棒手势识别使用多个形状导向的视觉线索

IF 2.4 4区计算机科学

Eurasip Journal on Image and Video Processing Pub Date : 2021-07-19 DOI: 10.1186/s13640-021-00567-1

Samy Bakheet, Ayoub Al-Hamadi

{"title":"Robust hand gesture recognition using multiple shape-oriented visual cues","authors":"Samy Bakheet, Ayoub Al-Hamadi","doi":"10.1186/s13640-021-00567-1","DOIUrl":"https://doi.org/10.1186/s13640-021-00567-1","url":null,"abstract":"Robust vision-based hand pose estimation is highly sought but still remains a challenging task, due to its inherent difficulty partially caused by self-occlusion among hand fingers. In this paper, an innovative framework for real-time static hand gesture recognition is introduced, based on an optimized shape representation build from multiple shape cues. The framework incorporates a specific module for hand pose estimation based on depth map data, where the hand silhouette is first extracted from the extremely detailed and accurate depth map captured by a time-of-flight (ToF) depth sensor. A hybrid multi-modal descriptor that integrates multiple affine-invariant boundary-based and region-based features is created from the hand silhouette to obtain a reliable and representative description of individual gestures. Finally, an ensemble of one-vs.-all support vector machines (SVMs) is independently trained on each of these learned feature representations to perform gesture classification. When evaluated on a publicly available dataset incorporating a relatively large and diverse collection of egocentric hand gestures, the approach yields encouraging results that agree very favorably with those reported in the literature, while maintaining real-time operation.","PeriodicalId":49322,"journal":{"name":"Eurasip Journal on Image and Video Processing","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2021-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138518861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Fast ISP coding mode optimization algorithm based on CU texture complexity for VVC 基于CU纹理复杂度的VVC ISP编码模式快速优化算法

IF 2.4 4区计算机科学

Eurasip Journal on Image and Video Processing Pub Date : 2021-07-02 DOI: 10.1186/s13640-021-00564-4

Zhi Liu, Mengjun Dong, Xiaohan Guan, Mengmeng Zhang, Ruoyu Wang

引用次数: 0

Spinal vertebrae localization and analysis on disproportionality in curvature using radiography—a comprehensive review 脊柱椎体定位及曲度不对称的影像学分析综述

IF 2.4 4区计算机科学

Eurasip Journal on Image and Video Processing Pub Date : 2021-06-29 DOI: 10.1186/s13640-021-00563-5

Joddat Fatima, Muhammad Usman Akram, Amina Jameel, Adeel Muzaffar Syed

{"title":"Spinal vertebrae localization and analysis on disproportionality in curvature using radiography—a comprehensive review","authors":"Joddat Fatima, Muhammad Usman Akram, Amina Jameel, Adeel Muzaffar Syed","doi":"10.1186/s13640-021-00563-5","DOIUrl":"https://doi.org/10.1186/s13640-021-00563-5","url":null,"abstract":"In human anatomy, the central nervous system (CNS) acts as a significant processing hub. CNS is clinically divided into two major parts: the brain and the spinal cord. The spinal cord assists the overall communication network of the human anatomy through the brain. The mobility of body and the structure of the whole skeleton is also balanced with the help of the spinal bone, along with reflex control. According to the Global Burden of Disease 2010, worldwide, back pain issues are the leading cause of disability. The clinical specialists in the field estimate almost 80% of the population with experience of back issues. The segmentation of the vertebrae is considered a difficult procedure through imaging. The problem has been catered by different researchers using diverse hand-crafted features like Harris corner, template matching, active shape models, and Hough transform. Existing methods do not handle the illumination changes and shape-based variations. The low-contrast and unclear view of the vertebrae also makes it difficult to get good results. In recent times, convolutional nnural Network (CNN) has taken the research to the next level, producing high-accuracy results. Different architectures of CNN such as UNet, FCN, and ResNet have been used for segmentation and deformity analysis. The aim of this review article is to give a comprehensive overview of how different authors in different times have addressed these issues and proposed different mythologies for the localization and analysis of curvature deformity of the vertebrae in the spinal cord.","PeriodicalId":49322,"journal":{"name":"Eurasip Journal on Image and Video Processing","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138518858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Exploiting prunability for person re-identification 利用可修剪性进行人员再识别

IF 2.4 4区计算机科学

Eurasip Journal on Image and Video Processing Pub Date : 2021-06-25 DOI: 10.1186/s13640-021-00562-6

Hugo Masson, Amran Bhuiyan, Le Thanh Nguyen-Meidine, Mehrsan Javan, P. Siva, Ismail Ben Ayed, Eric Granger

引用次数: 1

Real-time embedded object detection and tracking system in Zynq SoC Zynq SoC中的实时嵌入式目标检测与跟踪系统

IF 2.4 4区计算机科学

Eurasip Journal on Image and Video Processing Pub Date : 2021-06-16 DOI: 10.1186/s13640-021-00561-7

Qingbo Ji, Chong Dai, Changbo Hou, Xun Li

{"title":"Real-time embedded object detection and tracking system in Zynq SoC","authors":"Qingbo Ji, Chong Dai, Changbo Hou, Xun Li","doi":"10.1186/s13640-021-00561-7","DOIUrl":"https://doi.org/10.1186/s13640-021-00561-7","url":null,"abstract":"With the increasing application of computer vision technology in autonomous driving, robot, and other mobile devices, more and more attention has been paid to the implementation of target detection and tracking algorithms on embedded platforms. The real-time performance and robustness of algorithms are two hot research topics and challenges in this field. In order to solve the problems of poor real-time tracking performance of embedded systems using convolutional neural networks and low robustness of tracking algorithms for complex scenes, this paper proposes a fast and accurate real-time video detection and tracking algorithm suitable for embedded systems. The algorithm combines the object detection model of single-shot multibox detection in deep convolution networks and the kernel correlation filters tracking algorithm, what is more, it accelerates the single-shot multibox detection model using field-programmable gate arrays, which satisfies the real-time performance of the algorithm on the embedded platform. To solve the problem of model contamination after the kernel correlation filters algorithm fails to track in complex scenes, an improvement in the validity detection mechanism of tracking results is proposed that solves the problem of the traditional kernel correlation filters algorithm not being able to robustly track for a long time. In order to solve the problem that the missed rate of the single-shot multibox detection model is high under the conditions of motion blur or illumination variation, a strategy to reduce missed rate is proposed that effectively reduces the missed detection. The experimental results on the embedded platform show that the algorithm can achieve real-time tracking of the object in the video and can automatically reposition the object to continue tracking after the object tracking fails.","PeriodicalId":49322,"journal":{"name":"Eurasip Journal on Image and Video Processing","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2021-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138518864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Single-frame super-resolution for remote sensing images based on improved deep recursive residual network 基于改进深度递归残差网络的遥感图像单帧超分辨率

IF 2.4 4区计算机科学

Eurasip Journal on Image and Video Processing Pub Date : 2021-05-24 DOI: 10.1186/s13640-021-00560-8

Jiali Tang, J. Zhang, Dan Chen, N. Al-Nabhan, Chenrong Huang

引用次数: 2