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Assessment framework for deepfake detection in real-world situations EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2024-02-13 Yuhang Lu, Touradj Ebrahimi
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Edge-aware nonlinear diffusion-driven regularization model for despeckling synthetic aperture radar images EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2024-01-11 Anthony Bua, Goodluck Kapyela, Libe Massawe, Baraka Maiseli
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Multimodal few-shot classification without attribute embedding EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2024-01-10 Jun Qing Chang, Deepu Rajan, Nicholas Vun
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Secure image transmission through LTE wireless communications systems EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2024-01-10 Farouk Abduh Kamil Al-Fahaidy, Radwan AL-Bouthigy, Mohammad Yahya H. Al-Shamri, Safwan Abdulkareem
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An optimized capsule neural networks for tomato leaf disease classification EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2024-01-08 Lobna M. Abouelmagd, Mahmoud Y. Shams, Hanaa Salem Marie, Aboul Ella Hassanien
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Multi-layer features template update object tracking algorithm based on SiamFC++ EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2024-01-04 Xiaofeng Lu, Xuan Wang, Zhengyang Wang, Xinhong Hei
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Robust steganography in practical communication: a comparative study EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2023-10-31 Tong Qiao, Shengwang Xu, Shuai Wang, Xiaoshuai Wu, Bo Liu, Ning Zheng, Ming Xu, Binmin Pan
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Multi-attention-based approach for deepfake face and expression swap detection and localization EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2023-08-18 Saima Waseem, Syed Abdul Rahman Syed Abu-Bakar, Zaid Omar, Bilal Ashfaq Ahmed, Saba Baloch, Adel Hafeezallah
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Semantic segmentation of textured mosaics EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2023-08-14 Melissa Cote, Amanda Dash, Alexandra Branzan Albu
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Comparison of synthetic dataset generation methods for medical intervention rooms using medical clothing detection as an example EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2023-08-02 Patrick Schülein, Hannah Teufel, Ronja Vorpahl, Indira Emter, Yannick Bukschat, Marcus Pfister, Nils Rathmann, Steffen Diehl, Marcus Vetter
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An early CU partition mode decision algorithm in VVC based on variogram for virtual reality 360 degree videos EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2023-05-22 Mengmeng Zhang, Yan Hou, Zhi Liu
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Learning a crowd-powered perceptual distance metric for facial blendshapes EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2023-05-15 Zeynep Cipiloglu Yildiz
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Studies in differentiating psoriasis from other dermatoses using small data set and transfer learning EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2023-05-15 Mariusz Nieniewski, Leszek J. Chmielewski, Sebastian Patrzyk, Anna Woźniacka
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Heterogeneous scene matching based on the gradient direction distribution field EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2023-04-27 Qingge Li, Ruitao Lu, Xiaogang Yang, Siyu Wang, Tong Shen, Wenxin Xia, Zhaoying Wei
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FitDepth: fast and lite 16-bit depth image compression algorithm EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2023-04-06 Juan P. D’Amato
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Vehicle logo detection using an IoAverage loss on dataset VLD100K-61 EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2023-04-05 Xiaohui Shi, Shengli Ma, Yang Shen, Yankun Yang, Zexin Tan
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Correction: Geolocation of covert communication entity on the Internet for post-steganalysis EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2023-03-13 Fan Zhang, Fenlin Liu, Xiangyang Luo
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Reversible designs for extreme memory cost reduction of CNN training EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2023-01-05 Tristan Hascoet, Quentin Febvre, Weihao Zhuang, Yasuo Ariki, Tetsuya Takiguchi
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Data and image storage on synthetic DNA: existing solutions and challenges EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2022-10-29 Melpomeni Dimopoulou, Marc Antonini
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A novel secured Euclidean space points algorithm for blind spatial image watermarking EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2022-09-23 Shaik Hedayath Basha, Jaison B
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Fine-grained precise-bone age assessment by integrating prior knowledge and recursive feature pyramid network EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2022-07-26 Yang Jia, Xinmeng Zhang, Hanrong Du, Weiguang Chen, Xiaohui Jin, Wei Qi, Bin Yang, Qiujuan Zhang, Zhi Wei
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Palpation localization of radial artery based on 3-dimensional convolutional neural networks EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2022-07-18 Qiliang Chen, Yulin Huang, Xing Zhu, Hong Lu, Zhongzhi Ji, Jiacheng Yang, Jingjing Luo
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Weakly supervised spatial–temporal attention network driven by tracking and consistency loss for action detection EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2022-07-18 Jinlei Zhu, Houjin Chen, Pan Pan, Jia Sun
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Performance analysis of different DCNN models in remote sensing image object detection EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2022-06-07 Huaijin Liu, Jixiang Du, Yong Zhang, Hongbo Zhang
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Multi-orientation local ternary pattern-based feature extraction for forensic dentistry EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2022-05-13 Karunya Rajmohan, Askarunisa Abdul Khader
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Face image synthesis from facial parts EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2022-05-10 Qiushi Sun, Jingtao Guo, Yi Liu
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An image-guided network for depth edge enhancement EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2022-04-15 Kuan-Ting Lee, En-Rwei Liu, Jar-Ferr Yang, Li Hong
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Automatic kidney segmentation using 2.5D ResUNet and 2.5D DenseUNet for malignant potential analysis in complex renal cyst based on CT images EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2022-03-22 Parin Kittipongdaja, Thitirat Siriborvornratanakul
Bosniak renal cyst classification has been widely used in determining the complexity of a renal cyst. However, it turns out that about half of patients undergoing surgery for Bosniak category III, take surgical risks that reward them with no clinical benefit at all. This is because their pathological results reveal that the cysts are actually benign not malignant. This problem inspires us to use recently
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Adaptive response maps fusion of correlation filters with anti-occlusion mechanism for visual object tracking EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2022-03-18 Jianming Zhang, Hehua Liu, Yaoqi He, Li-Dan Kuang, Xi Chen
Despite the impressive performance of correlation filter-based trackers in terms of robustness and accuracy, the trackers have room for improvement. The majority of existing trackers use a single feature or fixed fusion weights, which makes it possible for tracking to fail in the case of deformation or severe occlusion. In this paper, we propose a multi-feature response map adaptive fusion strategy
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Random CNN structure: tool to increase generalization ability in deep learning EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2022-02-08 Bartosz Swiderski, Stanislaw Osowski, Grzegorz Gwardys, Jaroslaw Kurek, Monika Slowinska, Iwona Lugowska
The paper presents a novel approach for designing the CNN structure of improved generalization capability in the presence of a small population of learning data. Unlike the classical methods for building CNN, we propose to introduce some randomness in the choice of layers with a different type of nonlinear activation function. The image processing in these layers is performed using either the ReLU
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Printing and scanning investigation for image counter forensics EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2022-02-07 Hailey James, Otkrist Gupta, Dan Raviv
Examining the authenticity of images has become increasingly important as manipulation tools become more accessible and advanced. Recent work has shown that while CNN-based image manipulation detectors can successfully identify manipulations, they are also vulnerable to adversarial attacks, ranging from simple double JPEG compression to advanced pixel-based perturbation. In this paper we explore another
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Reduced reference image and video quality assessments: review of methods EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2022-01-12 Dost, Shahi, Saud, Faryal, Shabbir, Maham, Khan, Muhammad Gufran, Shahid, Muhammad, Lovstrom, Benny
With the growing demand for image and video-based applications, the requirements of consistent quality assessment metrics of image and video have increased. Different approaches have been proposed in the literature to estimate the perceptual quality of images and videos. These approaches can be divided into three main categories; full reference (FR), reduced reference (RR) and no-reference (NR). In
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Perceptual hashing method for video content authentication with maximized robustness EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-11-21 Ma, Qiang, Xing, Ling
Perceptual video hashing represents video perceptual content by compact hash. The binary hash is sensitive to content distortion manipulations, but robust to perceptual content preserving operations. Currently, boundary between sensitivity and robustness is often ambiguous and it is decided by an empirically defined threshold. This may result in large false positive rates when received video is to
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A study on implementation of real-time intelligent video surveillance system based on embedded module EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-11-21 Kim, Jin Su, Kim, Min-Gu, Pan, Sung Bum
Conventional surveillance systems for preventing accidents and incidents do not identify 95% thereof after 22 min when one person monitors a plurality of closed circuit televisions (CCTV). To address this issue, while computer-based intelligent video surveillance systems have been studied to notify users of abnormal situations when they happen, it is not commonly used in real environment because of
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HR-MPF: high-resolution representation network with multi-scale progressive fusion for pulmonary nodule segmentation and classification EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-11-13 Zhu, Ling, Zhu, Hongqing, Yang, Suyi, Wang, Pengyu, Yu, Yang
Accurate segmentation and classification of pulmonary nodules are of great significance to early detection and diagnosis of lung diseases, which can reduce the risk of developing lung cancer and improve patient survival rate. In this paper, we propose an effective network for pulmonary nodule segmentation and classification at one time based on adversarial training scheme. The segmentation network
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Fatigue driving detection based on electrooculography: a review EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-11-02 Tian, Yuanyuan, Cao, Jingyu
To accurately identify fatigued driving, establishing a monitoring system is one of the important guarantees of improving traffic safety and reducing traffic accidents. Among many research methods, electrooculogram signal (EOG) has unique advantages. This paper presents a systematic literature review of these technologies and summarizes a basic framework of fatigue driving monitoring system based on
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Benchmark for anonymous video analytics EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-10-07 Sanchez-Matilla, Ricardo, Cavallaro, Andrea
Out-of-home audience measurement aims to count and characterize the people exposed to advertising content in the physical world. While audience measurement solutions based on computer vision are of increasing interest, no commonly accepted benchmark exists to evaluate and compare their performance. In this paper, we propose the first benchmark for digital out-of-home audience measurement that evaluates
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Recognition of printed small texture modules based on dictionary learning EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-09-29 Yu, Lifang, Cao, Gang, Tian, Huawei, Cao, Peng, Zhang, Zhenzhen, Shi, Yun Q.
Quick Response (QR) codes are designed for information storage and high-speed reading applications. To store additional information, Two-Level QR (2LQR) codes replace black modules in standard QR codes with specific texture patterns. When the 2LQR code is printed, texture patterns are blurred and their sizes are smaller than\(0.5{\mathrm{cm}}^{2}\). Recognizing small-sized blurred texture patterns
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Performance enhancement method for multiple license plate recognition in challenging environments EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-09-17 Khan, Khurram, Imran, Abid, Rehman, Hafiz Zia Ur, Fazil, Adnan, Zakwan, Muhammad, Mahmood, Zahid
Multiple-license plate recognition is gaining popularity in the Intelligent Transport System (ITS) applications for security monitoring and surveillance. Advancements in acquisition devices have increased the availability of high definition (HD) images, which can capture images of multiple vehicles. Since license plate (LP) occupies a relatively small portion of an image, therefore, detection of LP
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Buffer evaluation model and scheduling strategy for video streaming services in 5G-powered drone using machine learning EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-08-23 Su, Yu, Wang, Shuijie, Cheng, Qianqian, Qiu, Yuhe
With regard to video streaming services under wireless networks, how to improve the quality of experience (QoE) has always been a challenging task. Especially after the arrival of the 5G era, more attention has been paid to analyze the experience quality of video streaming in more complex network scenarios (such as 5G-powered drone video transmission). Insufficient buffer in the video stream transmission
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Superresolution reconstruction method for ancient murals based on the stable enhanced generative adversarial network EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-07-30 Cao, Jianfang, Jia, Yiming, Yan, Minmin, Tian, Xiaodong
A stable enhanced superresolution generative adversarial network (SESRGAN) algorithm was proposed in this study to address the low-resolution and blurred texture details in ancient murals. This algorithm makes improvements on the basis of GANs, which use dense residual blocks to extract image features. After two upsampling steps, the feature information of the image is input into the high-resolution
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Trademark infringement recognition assistance system based on human visual Gestalt psychology and trademark design EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-07-22 Kuo-Ming Hung, Li-Ming Chen, Ting-Wen Chen
Trademarks are common graphic signs in human society. People used this kind of graphic sign to distinguish the signs of representative significance such as individuals, organizations, countries, and groups. Under effective use, these graphic signs can bring maintenance and development resources and profits to the owner. In addition to maintenance and development, organizations that have obtained resources
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Robust hand gesture recognition using multiple shape-oriented visual cues EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-07-19 Samy Bakheet, Ayoub Al-Hamadi
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
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Pansharpening based on convolutional autoencoder and multi-scale guided filter EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-07-19 Ahmad AL Smadi, Shuyuan Yang, Zhang Kai, Atif Mehmood, Min Wang, Ala Alsanabani
In this paper, we propose a pansharpening method based on a convolutional autoencoder. The convolutional autoencoder is a sort of convolutional neural network (CNN) and objective to scale down the input dimension and typify image features with high exactness. First, the autoencoder network is trained to reduce the difference between the degraded panchromatic image patches and reconstruction output
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Fast ISP coding mode optimization algorithm based on CU texture complexity for VVC EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-07-02 Zhi Liu, Mengjun Dong, Xiao Han Guan, Mengmeng Zhang, Ruoyu Wang
In lately published video coding standard Versatile Video Coding (VVC/ H.266), the intra sub-partitions (ISP) coding mode is proposed. It is efficient for frames with rich texture, but less efficient for frames that are very flat or constant. In this paper, by comparing and analyzing the rate distortion cost (RD-cost) of coding unit (CU) with different texture features for using and not using ISP(No-ISP)
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Spinal vertebrae localization and analysis on disproportionality in curvature using radiography—a comprehensive review EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-06-29 Joddat Fatima, Muhammad Usman Akram, Amina Jameel, Adeel Muzaffar Syed
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
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Exploiting prunability for person re-identification EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-06-25 Hugo Masson, Amran Bhuiyan, Le Thanh Nguyen-Meidine, Mehrsan Javan, Parthipan Siva, Ismail Ben Ayed, Eric Granger
Recent years have witnessed a substantial increase in the deep learning (DL) architectures proposed for visual recognition tasks like person re-identification, where individuals must be recognized over multiple distributed cameras. Although these architectures have greatly improved the state-of-the-art accuracy, the computational complexity of the convolutional neural networks (CNNs) commonly used
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Real-time embedded object detection and tracking system in Zynq SoC EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-06-16 Qingbo Ji, Chong Dai, Changbo Hou, Xun Li
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
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Single-frame super-resolution for remote sensing images based on improved deep recursive residual network EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-05-24 Jiali Tang, Jie Zhang, Dan Chen, Najla Al-Nabhan, Chenrong Huang
Single-frame image super-resolution (SISR) technology in remote sensing is improving fast from a performance point of view. Deep learning methods have been widely used in SISR to improve the details of rebuilt images and speed up network training. However, these supervised techniques usually tend to overfit quickly due to the models’ complexity and the lack of training data. In this paper, an Improved
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Single image super resolution based on multi-scale structure and non-local smoothing EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-05-17 Wenyi Wang, Jun Hu, Xiaohong Liu, Jiying Zhao, Jianwen Chen
In this paper, we propose a hybrid super-resolution method by combining global and local dictionary training in the sparse domain. In order to present and differentiate the feature mapping in different scales, a global dictionary set is trained in multiple structure scales, and a non-linear function is used to choose the appropriate dictionary to initially reconstruct the HR image. In addition, we
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Quaternion fractional-order color orthogonal moment-based image representation and recognition EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-05-17 Bing He, Jun Liu, Tengfei Yang, Bin Xiao, Yanguo Peng
Inspired by quaternion algebra and the idea of fractional-order transformation, we propose a new set of quaternion fractional-order generalized Laguerre orthogonal moments (QFr-GLMs) based on fractional-order generalized Laguerre polynomials. Firstly, the proposed QFr-GLMs are directly constructed in Cartesian coordinate space, avoiding the need for conversion between Cartesian and polar coordinates;
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OSDDY: embedded system-based object surveillance detection system with small drone using deep YOLO EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-05-17 Kaliappan Madasamy, Vimal Shanmuganathan, Vijayalakshmi Kandasamy, Mi Young Lee, Manikandan Thangadurai
Computer vision is an interdisciplinary domain for object detection. Object detection relay is a vital part in assisting surveillance, vehicle detection and pose estimation. In this work, we proposed a novel deep you only look once (deep YOLO V3) approach to detect the multi-object. This approach looks at the entire frame during the training and test phase. It followed a regression-based technique
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Approximate calculation of 8-point DCT for various scenarios of practical applications EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-05-17 Dariusz Puchala
In this paper, based on the parametric model of the matrix of discrete cosine transform (DCT), and using an exhaustive search of the parameters’ space, we seek for the best approximations of 8-point DCT at the given computational complexities by taking into account three different scenarios of practical usage. The possible parameter values are selected in such a way that the resulting transforms are
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Non-frontal facial expression recognition based on salient facial patches EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-05-12 Bin Jiang, Qiuwen Zhang, Zuhe Li, Qinggang Wu, Huanlong Zhang
Methods using salient facial patches (SFPs) play a significant role in research on facial expression recognition. However, most SFP methods use only frontal face images or videos for recognition, and they do not consider head position variations. We contend that SFP can be an effective approach for recognizing facial expressions under different head rotations. Accordingly, we propose an algorithm,
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A probabilistic segmentation and entropy-rank correlation-based feature selection approach for the recognition of fruit diseases EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-05-10 Muhammad Attique Khan, Tallha Akram, Muhammad Sharif, Majed Alhaisoni, Tanzila Saba, Nadia Nawaz
Agriculture plays a critical role in the economy of several countries, by providing the main sources of income, employment, and food to their rural population. However, in recent years, it has been observed that plants and fruits are widely damaged by different diseases which cause a huge loss to the farmers, although this loss can be minimized by detecting plants’ diseases at their earlier stages
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An enhanced binarization framework for degraded historical document images EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-05-10 Wei Xiong, Lei Zhou, Ling Yue, Lirong Li, Song Wang
Binarization plays an important role in document analysis and recognition (DAR) systems. In this paper, we present our winning algorithm in ICFHR 2018 competition on handwritten document image binarization (H-DIBCO 2018), which is based on background estimation and energy minimization. First, we adopt mathematical morphological operations to estimate and compensate the document background. It uses
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Segmentation of epithelial human type 2 cell images for the indirect immune fluorescence based on modified quantum entropy EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-04-23 Abu-Zinadah Hanaa, Abdel Azim Gamil
The autoimmune disorders such as rheumatoid, arthritis, and scleroderma are connective tissue diseases (CTD). Autoimmune diseases are generally diagnosed using the antinuclear antibody (ANA) blood test. This test uses indirect immune fluorescence (IIf) image analysis to detect the presence of liquid substance antibodies at intervals the blood, which is responsible for CTDs. Typically human alveolar
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Refinement of matching costs for stereo disparities using recurrent neural networks EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-04-06 Alper Emlek, Murat Peker
Depth is essential information for autonomous robotics applications that need environmental depth values. The depth could be acquired by finding the matching pixels between stereo image pairs. Depth information is an inference from a matching cost volume that is composed of the distances between the possible pixel points on the pre-aligned horizontal axis of stereo images. Most approaches use matching
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Stacked generative adversarial networks for image compositing EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-03-29 Bing Yu, Youdong Ding, Zhifeng Xie, Dongjin Huang
Perfect image compositing can harmonize the appearance between the foreground and background effectively so that the composite result looks seamless and natural. However, the traditional convolutional neural network (CNN)-based methods often fail to yield highly realistic composite results due to overdependence on scene parsing while ignoring the coherence of semantic and structural between foreground
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Evaluating effects of focal length and viewing angle in a comparison of recent face landmark and alignment methods EURASIP J. Image Video Process. (IF 2.4) Pub Date : 2021-03-29 Xiang Li, Jianzheng Liu, Jessica Baron, Khoa Luu, Eric Patterson
Recent attention to facial alignment and landmark detection methods, particularly with application of deep convolutional neural networks, have yielded notable improvements. Neither these neural-network nor more traditional methods, though, have been tested directly regarding performance differences due to camera-lens focal length nor camera viewing angle of subjects systematically across the viewing