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Detection of Logos of Moving Vehicles under Complex Lighting Conditions

Qiang Zhao, Wenhao Guo
2022 Applied Sciences  
For images acquired in complex light conditions, adaptive image enhancement is used to improve the accuracy of car sign detection by more than 2%; for the problems of multi-scale and detection speed of  ...  This study proposes a method for vehicle logo detection and recognition to detect missing and inaccurate vehicle marks under complex lighting conditions.  ...  As shown in Table 2 , YOLOF outperforms the Faster R-CNN model for multi-scale vehicle logo image detection [26, 43] ; compared with the original YOLOF algorithm, the accuracy of the improved YOLOF algorithm  ... 
doi:10.3390/app12083835 fatcat:l3uexrlzy5h6vht47bqp3vbddq

An Effective and Robust Detector for Logo Detection [article]

Xiaojun Jia, Huanqian Yan, Yonglin Wu, Xingxing Wei, Xiaochun Cao, Yong Zhang
2021 arXiv   pre-print
In detail, we extend detectoRS algorithm to a cascade schema with an equalization loss function, multi-scale transformations, and adversarial data augmentation.  ...  To overcome this problem, a novel logo detector based on the mechanism of looking and thinking twice is proposed in this paper for robust logo detection.  ...  More concretely, we extend detectoRS algorithm to a cascade schema with an equalization loss function, multi-scale transforms, and adversarial data augmentation.  ... 
arXiv:2108.00422v1 fatcat:htk4wjkg2na5lbxh3rydlb5ooq

Single Stage Vehicle Logo Detector Based on Multi-Scale Prediction

Junxing ZHANG, Shuo YANG, Chunjuan BO, Huimin LU
2020 IEICE transactions on information and systems  
Experimental results show that the accuracy and speed of the detection algorithm are improved for the object of small sizes. key words: vehicle logo detection, VLD-45-S, single-stage detector, multiscale  ...  In order to solve the problem that the training samples are scarce, our work in this paper is improved by constructing the data of a vehicle logo (VLD-45-S), multistage pre-training, multi-scale prediction  ...  Since the size of vehicle logo is so small compared to the target of ImageNet, we have to adapt the network of feature extraction to representation the object of vehicle logo.  ... 
doi:10.1587/transinf.2020edp7088 fatcat:rmi4pyxe5nczzgq6sz6k7yfopq

A Novel Robust Watermarking Technique Based on Nonsubsampled Contourlet Transform and SVD

C.Venkata Narasimhulu, K Satya Prasad
2011 The International Journal of Multimedia & Its Applications  
The NSCT can give the asymptotic optimal representation of the edges and contours in image by virtue of the characteristics of good multi resolution shift invariance and multi directionality.  ...  KEYWORDS Image watermarking, nonsubsampled contourlet transform, SVD, visual watermark logo.  ...  A watermarking algorithm consists of watermark structure, an embedding algorithm and extraction or detection algorithm.  ... 
doi:10.5121/ijma.2011.3104 fatcat:hagd2vrdo5gajk5dujhlciypaa

A Robust Watermarking Technique based on Nonsubsampled Contourlet Transform and SVD

C.Venkata Narasimhulu, K.Satya Prasad
2011 International Journal of Computer Applications  
The NSCT can give the asymptotic optimal representation of the edges and contours in image by virtue of the characteristics of good multi resolution shift invariance and multi directionality.  ...  KEYWORDS Image watermarking, nonsubsampled contourlet transform, SVD, visual watermark logo.  ...  A watermarking algorithm consists of watermark structure, an embedding algorithm and extraction or detection algorithm.  ... 
doi:10.5120/2032-2642 fatcat:mo53bgnurrds3on3rsssymg2ty

A Deep One-Shot Network for Query-based Logo Retrieval [article]

Ayan Kumar Bhunia, Ankan Kumar Bhunia, Shuvozit Ghose, Abhirup Das, Partha Pratim Roy, Umapada Pal
2019 arXiv   pre-print
Feature matching between the latent query representation and multi-scale feature maps of segmentation branch using simple concatenation operation followed by 1x1 convolution layer makes our model scale-invariant  ...  Logo detection in real-world scene images is an important problem with applications in advertisement and marketing.  ...  In the meantime, several object detection algorithms have been introduced, namely, R-CNN [13] , Fast R-CNN [14] and Faster R-CNN [4] which have been successfully adapted for the logo detection problem  ... 
arXiv:1811.01395v4 fatcat:45e44rw3i5a3pddklcsmpt56pq

Character index

2011 2011 IEEE International Conference on Multimedia and Expo  
doi:10.1109/icme.2011.6011827 fatcat:wjy7yvkmvbbf3hj4wbyjapx5gu

Improving Small Object Proposals for Company Logo Detection

Christian Eggert, Dan Zecha, Stephan Brehm, Rainer Lienhart
2017 Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval - ICMR '17  
Faster R-CNN is such an approach for object detection which combines both stages into a single pipeline. In this paper we apply Faster R-CNN to the task of company logo detection.  ...  Based on theoretical considerations, we introduce an improved scheme for generating anchor proposals and propose a modification to Faster R-CNN which leverages higher-resolution feature maps for small  ...  Especially, we would like to express our gratitude for their help in re-annotating the FlickrLogos dataset.  ... 
doi:10.1145/3078971.3078990 dblp:conf/mir/EggertZBL17 fatcat:ejqqnntt7jdapftiobfvlnne6a

Logo Detection Based on FCM Clustering Algorithm and Texture Features [chapter]

Wala Zaaboub, Lotfi Tlig, Mounir Sayadi, Basel Solaiman
2020 Lecture Notes in Computer Science  
Specifically we propose a novel approach for administrative logo detection based on a fuzzy classification with a multi-fractal texture feature, capable of automatically characterizing texture measures  ...  Logo detection methods usually depend on logo shapes and need for training data or a-priori information on the processed images. This limits their effectiveness to real-world applications.  ...  In addition, for logos contained near-scattered components, an ordinary extraction algorithm is typically unable to detect all these components.  ... 
doi:10.1007/978-3-030-51935-3_35 fatcat:4nxincjzsjbgjfioimubiypyca

An Adaptive Digital Image Watermarking Algorithm Based on Morphological Haar Wavelet Transform

Xiaosheng Huang, Sujuan Zhao
2012 Physics Procedia  
In the algorithm, the original image and the watermark image are decomposed with multi-scale morphological wavelet transform respectively.  ...  In this paper, we propose an adaptive digital image watermarking algorithm based on non-linear wavelet transform--Morphological Haar Wavelet Transform.  ...  The simulation shows that our algorithm has better capacity of adaptive, robustness and security.  ... 
doi:10.1016/j.phpro.2012.03.127 fatcat:3fxiwkeg5ncpnmjn5pal5bo4mi

Front Matter: Volume 10615

Hui Yu, Junyu Dong
2018 Ninth International Conference on Graphic and Image Processing (ICGIP 2017)  
The publisher is not responsible for the validity of the information or for any outcomes resulting from reliance thereon.  ... Paper Numbering: Proceedings of SPIE follow an e-First publication model. A unique citation identifier (CID) number is assigned to each article at the time of publication.  ...  sparse representation [10615-80] 10615 35 Adaptive structured dictionary learning for image fusion based on group-sparse- representation [10615-215] 10615 36 An efficient method for the fusion of  ... 
doi:10.1117/12.2316542 fatcat:tdaw76jq6nehpnttiga2lcuhna

Multi-perspective cross-class domain adaptation for open logo detection

Hang Su, Shaogang Gong, Xiatian Zhu
2020 Computer Vision and Image Understanding  
To generalise and transfer knowledge of fully supervised logo classes to other 1-shot icon supervised classes, we propose a Multi-Perspective Cross-Class (MPCC) domain adaptation method.  ...  Existing logo detection methods mostly rely on supervised learning with a large quantity of labelled training data in limited classes.  ...  Commonly, these methods focus on supervised learning with the need for accurately labelling fine-grained object- To scale up the learning algorithms, Su et al. (2017a) propose to leverage the rich web  ... 
doi:10.1016/j.cviu.2020.103156 fatcat:o42uzsff2rd4rkpjurvugcpn6a

The Multi-scale Microstructure Binary Pattern Extraction and Learning for Image Representation

Dongbo Zhang, Lianglin Yi, Hongzhong Tang, Ying Zhang, Haixia Xu
2019 IET Image Processing  
In this study, an image representation method based on multi-scale microstructural binary pattern extraction is proposed, which uses zero-mean microstructural pattern binarisation.  ...  , and representation ability.  ...  An example of ZMMPB pattern extraction for performing 1 × 1 scale blocking of an image is shown in Fig. 2 .  ... 
doi:10.1049/iet-ipr.2018.6358 fatcat:ro7rt7bap5d2hcfyq5ltof3zqu

Multi-object image retrieval based on shape and topology

Naif Alajlan, Mohamed S. Kamel, George Freeman
2006 Signal processing. Image communication  
For this purpose, we adapt a continuous optimization approach to solve the MSSI problem and a very effective dynamic programming algorithm to measure the similarity between the attributed nodes.  ...  We aim at developing a geometry-based retrieval system for multi-object images.  ...  Anil Jain for providing the logo images. We also thank the anonymous reviewers for their valuable comments.  ... 
doi:10.1016/j.image.2006.09.002 fatcat:ovcbbuxaxfefdjyh2jmqvi4mjy

Robust Vehicle Speed Measurement Based on Feature Information Fusion for Vehicle Multi-Characteristic Detection

Lei Yang, Jianchen Luo, Xiaowei Song, Menglong Li, Pengwei Wen, Zixiang Xiong
2021 Entropy  
An improved ECA-YOLOv4 object detection algorithm based on both feature information fusion and cross channel interaction is proposed, which improves the performance of YOLOv4 for vehicle multi-characteristic  ...  A vehicle multi-characteristic dataset is constructed. With this dataset, seven CNN-based modern object detection algorithms are trained for vehicle multi-characteristic detection.  ...  algorithm based on FPN is suitable for this multi-scale varying object detection problem.  ... 
doi:10.3390/e23070910 fatcat:wwwxk3s3xbdxdd3ev4kbi5rap4
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