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Yarn-Dyed Fabric Image Retrieval Using Colour Moments and the perceptual hash algorithm

FIBRES & TEXTILES IN EASTERN EUROPE 2019年第5期27卷 39-46页

作者： Li, Zhongjian Xiang, Jun Wang, Lei Zhang, Ning Pan, Ruru Gao, Weidong Jiangnan Univ Sch Text & Clothing Minist Educ Key Lab Ecotext 1800 Lihu Rd Wuxi 214122 Jiangsu Peoples R China

Due to the variety of yarn colours and arrangement, it is a challenging problem to retrieve a yarn-dyed fabric image. In this paper, yarn-dyed fabric samples are captured by the DigiEye system first, and then pattern images of the fabric images captured are simulated by pattern design software based on extracted structure parameters of the yarn-dyed fabric. For the simulated pattern image, an effective algorithm is proposed to retrieve these kinds of images by combining the colour moments method and perceptual hash algorithm. Then the pattern images retrieved are mapped back to the yarn-dyed fabric image so as to realise the yarn-dyed fabric image retrieval. In the algorithm proposed, the colour moments method is adopted to extract the colour features, and the perceptual hash algorithm is utilised to calculate the spatial features of the simulated pattern images. Then the two kinds of image features are used to compute the similarity between the input original image and each target image based on the Euclidean distance and Hamming distance. Relevant images can be retrieved in dependence on the similarity value, which is determined by calculating the optimum weighted value of the colour features' similarity and spatial features' similarity. In order to measure the retrieval efficiency of the method proposed, the accuracy rate and retrieval rate of image retrieval were computed in experiments using a PATTERN image database with 300 images. The experimental results show that the average accuracy rate of the method proposed is 85.30% and the retrieval rate - 53.51% when the weighted value of the colour feature similarity is fixed at 0.45 and the spatial featur similarity is 0.55. It is shown that the method presented is effective to retrieve pattern images of yarn-dyed fabric.

关键词： yarn-dyed fabric image retrieval colour moments perceptual hash algorithm Hamming distance

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Accurate facial expression recognition method based on perceptual hash algorithm

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INTERNATIONAL JOURNAL OF BIOMETRICS 2024年第3-4期16卷 364-380页

作者： Yang, Yang Henan Univ Econ & Law Ctr Educ Technol Zhengzhou 450046 Peoples R China Henan Univ Sch Educ Zhengzhou 450046 Peoples R China

To improve recognition accuracy, a precise facial expression recognition method based on perceptual hash algorithm is proposed. Firstly, the single scale Retinex algorithm is used to enhance facial expression images. The image is divided into high-frequency and low-frequency parts through curvature change decomposition, and the image is enhanced after filtering processing. Secondly, the two-dimensional principal component analysis network is combined with a perceptual hash algorithm based on a simplified Watson model to extract image features. Finally, the feature is added to the hash table, and based on the distance between the feature and the facial expression to be recognised, the nearest neighbour of the facial expression to be recognised is judged to achieve accurate facial expression recognition. The experimental results show that the face recognition accuracy of this method reaches over 95%, indicating that its recognition effect is good.

关键词： perceptual hash algorithm facial expression recognition image enhancement feature extraction hashtable

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Applications of perceptual hash algorithm in Agriculture Images

Applications of Perceptual Hash Algorithm in Agriculture Ima...

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6th International Congress on Image and Signal Processing (CISP)

作者： Liu, Xin Zhang, Qian Luan, RuPeng Yu, Feng Beijing Acad Agr & Forestry Sci Inst Agr Scientech Informat Beijing Peoples R China

ISBN: (纸本)9781479927630

According to the characteristics of agriculture image, new image recognition scheme and image authentication scheme were designed, which based on perceptual hash algorithm. Some tomato leaf diseases pictures were used to achieve image perceptual hash feature extraction. And the experimental results show that the same diseases images have closer perceptual hash characteristics.

关键词： perceptual hash algorithm agriculture image processing image retrieval image recognition image authentication

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Histogram-based perceptual hash algorithm for synthetic aperture radar image segmentation

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JOURNAL OF ELECTRONIC IMAGING 2018年第3期27卷 033044-033044页

作者： Ji, Jian Han, Linyi Wei, Jiajie Lu, Xiaojia Li, Xiaoyuan Xidian Univ Sch Comp Sci & Technol Comp Applicat Technol Xian Shaanxi Peoples R China Sci & Technol Informat Syst Engn Lab Nanjing Jiangsu Peoples R China

To speed up the segmentation procedure and improve the segmentation quality of synthetic aperture radar (SAR) image, this paper presents an adaptive unsupervised SAR image segmentation method, which is integrated in the grayscale histogram and perceptual hash algorithm. The final clusters can be acquired self-adaptively without predefining. The two stages of the algorithm are discussed in details: histogram-based preprocessing and region merging. In preprocessing, histogram-based gray-level reduction is adopted to generate the set of initial segmented regions to address the problem of over-segmentation. When merging regions, the similarity of different regions can be obtained by comparing their different fingerprints calculated in the perceptual hash algorithm, which is the kernel of the whole SAR image segmentation method. The application of the perceptual hash algorithm for image segmentation can reduce the computational complexity and improve the efficiency of region merging. Experimental simulations and theoretical analysis are used to demonstrate the effectiveness of this algorithm. (c) 2018 SPIE and IS&T

关键词： gray-level reduction perceptual hash algorithm synthetic aperture radar image segmentation

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Adaptive Compressive Tracking Based on perceptual hash algorithm

Adaptive Compressive Tracking Based on Perceptual Hash Algor...

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2017 2nd International Conference on Information Technology and Management Engineering（ITME 2017）

作者： Lei ZHANG Zheng-guang XIE Hong-jun LI School of Electronic Information Nantong University

As the compressive tracking algorithm is easily failed to track target due to the classifier learning rate is fixed when appearances and lightings of target get seriously changed and completely loses the target after heavy occlusion, we propose adaptive compressive tracking algorithm based on perceptual hash algorithm. It makes the compressive tracking algorithm more adaptive to the change of target appearances by adjusting the learning rate of classifier in real time according to the Hamming distance between the hash fingerprints of current target and the original one. Experimental results show that the method can quickly and accurately track the target in the case of the object appearances change and the object is occluded. Our tracker accuracy and robustness have been improved and real-time performance.

关键词： Compressive Tracking perceptual hash algorithm Real-time Performance

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Novel 3-D hyperchaotic map with hidden attractor and its application in meaningful image encryption

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NONLINEAR DYNAMICS 2023年第20期111卷 19487-19512页

作者： Hu, Xin Jiang, Donghua Ahmad, Musheer Tsafack, Nestor Zhu, Liya Zheng, Mingwen Changan Univ Sch Energy & Elect Engn Xian 710064 Peoples R China Sun Yat Sen Univ Sch Comp Sci & Engn Guangzhou 511400 Peoples R China Jamia Millia Islamia Dept Comp Engn New Delhi 110025 India Univ Dschang Elect Engn Dept IUT FV Bandjoun Cameroon Changan Univ Sch Elect & Control Engn Xian 710064 Peoples R China Shandong Univ Technol Sch Math & Stat Zibo 255012 Peoples R China

To enhance the performance limitations of existing image encryption schemes using compressive sensing (CS) technique in withstanding plaintext analysis-based security attack models, a new feasible solution is proposed in this paper. First, on the premise that the discrete wavelet packet transform (WPT) matrix which is incoherent with the measurement matrix constructed by the Xorshift algorithm is selected as the sparse basis matrix, an asymmetric compressive sensing model is designed by combining semi-tensor product operation and matrix transform. Then, the plaintext sparse coefficients are compacted and encrypted by this novel compression model and bidirectional hybrid diffusion algorithm. Next, the secret data without semantic features are hidden into the publicly available carrier image by the Haar transform (HT) embedding in the novel orthogonal YCbCr color space. Wherein, to relieve chaotic dynamics degradation phenomenon caused by the finite word-length (FWL) effect, a novel 3-D bounded non-linear map (3-BNM) with hyperchaotic properties is introduced to construct the highly unpredictable secret code streams with the assistance of the perceptual hash algorithm (PHA). Eventually, the performance analysis and comparative experiments demonstrate that the proposed encryption scheme is capable of passing multiple security tests and outperforming the recently proposed schemes.

关键词： Image encryption Compressive sensing Hyperchaotic map Haar transform perceptual hash algorithm

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Long-term tracking method on ground moving target of UAV 6

Long-term tracking method on ground moving target of UAV

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IEEE Chinese Guidance, Navigation and Control Conference (CGNCC)

作者： Gao, Qingji Zeng, Zheng Chao Hu, Dandan Civil Aviat Univ China Inst Robot Comp Sci & Technol Tianjin 300300 Peoples R China Civil Aviat Univ China Aviat Inst Automat Sch Nav Guidance & Control Tianjin 300300 Peoples R China Civil Aviat Univ China Inst Robot Control Theory & Control Engn Tianjin 300300 Peoples R China

ISBN: (纸本)9781479946990

The 7th IARC (international aerial robot competition) focus on a long-term and real-time tracking of ground moving target for UAV (unmanned aerial vehicle). This paper proposes a tracking method using Camshift algorithm with color and edge features fusion, which will apply a Phash target detection algorithm basing on perceptual hash algorithm. Supposing targets are severely obscured or disappear from view, which will lead tracking failure, whereas targets can be detected and obtained again using the method. Experimental results demonstrate that this method can provide a long-term and real-time tracking of ground moving target, which processes both robustness and computational efficiency.

关键词： UAV Target tracking Camshift perceptual hash algorithm

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CNN Hyperparameter Optimization Based on CNN Visualization and Perception hash algorithm 19

CNN Hyperparameter Optimization Based on CNN Visualization a...

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19th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)

作者： Wang, Yifeng Wang, Yang Li, Hongyi Cai, Zhuoxi Tang, Xiaohan Yang, Yin Harbin Inst Technol Sch Sci Shenzhen Peoples R China

ISBN: (纸本)9781728197241

In this paper, the network structure and the optimal hyperparameter selection which affect the performance of the model are obtained through the analysis of the convolutional neural network model with mathematical interpretation and visualization. In the study, we used visual methods such as deconvolution and Guided Grad-CAM to display the network structure, parameter changes, and the learning process of the model convolutional layer. Simultaneously, we developed CNN hyperparameters optimization strategy based on the perceptual hash algorithm according to its training characteristics. This method significantly improves the accuracy of image classification of the model and the generalization ability of the model and also provides certain theoretical support for the optimization and understanding of deep learning models in practical application. In addition, the hyperparameter optimization method based on the deep learning model feature map reconstruction visualization proposed in this paper also provides a good idea for the formulation of model training strategies.

关键词： convolutional neural network visualization interpretation hyperparameters optimization perceptual hash algorithm

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Tool Wearing Prediction by Using CNC Spindle Current Data 5

Tool Wearing Prediction by Using CNC Spindle Current Data

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5th IEEE Eurasia Conference on IOT, Communication and Engineering, ECICE 2023

作者： Cheng, Yen Hao Shen, Jing Chung Smart Machinery and Intelligent Manufacturing Research Center Department of Automation Engineering Yunlin Taiwan

ISBN: (纸本)9798350314694

In this research, we obtained characteristic values of CNC load current through the CNC machining process. We used the perceptual hash algorithm and the Correlation Coefficient method to separately establish similarity scores for each model. Big data was then introduced to analyze and classify these two scores. When the load current correlation exceeded a predefined threshold, a good model was used. Conversely, if it fell below the threshold, the opposite was true. Additionally, we established a database for the degree of tool wear through visual measuring instruments to verify its correlation with load current. © 2023 IEEE.

关键词： ai automatic modeling correlation coefficient method image similarity detection perceptual hash algorithm

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CNN Hyperparameter Optimization Based on CNN Visualization and Perception hash algorithm

CNN Hyperparameter Optimization Based on CNN Visualization a...

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第十九届分布式计算及其应用国际学术研讨会

作者： Yifeng Wang Yang Wang Hongyi Li Zhuoxi Cai Xiaohan Tang Yin Yang School of Science Harbin Institute of Technology

关键词： convolutional neural network visualization interpretation hyperparameters optimization perceptual hash algorithm

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