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Ultrasound Speckle Reduction Based on histogram Curve matching and Region Growing

Computers, Materials & Continua 2020年第10期65卷 705-722页

作者： Jinrong Hu Zhiqin Lei Xiaoying Li Yongqun He Jiliu Zhou Department of Computer Science Chengdu University of Information TechnologyChengdu610225China Institute of Medical Information Chinese Academy of Medical SciencesBeijing100020China Medical School University of MichiganMichigan48109-0168USA

The quality of ultrasound scanning images is usually damaged by speckle *** paper proposes a method based on local statistics extracted from a histogram to reduce ultrasound speckle through a region growing *** single statistical moment-based speckle reduction algorithms,this method adaptively smooths the speckle regions while preserving the margin and tissue structure to achieve high *** criterion of a speckle region is defined by the similarity value obtained by matching the histogram of the current processing window and the reference window derived from the speckle region in ***,according to the similarity value and tissue characteristics,the entire image is divided into several levels of speckle-content regions,and adaptive smoothing is performed based on these classification characteristics and the corresponding window size determined by the proposed region growing *** conducted from phantoms and in vivo images have shown very promising results after a quantitative and qualitative comparison with existing work.

关键词： Ultrasound speckle histogram matching speckle reduction tissue characterization region growing

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histogram Matched Chest X-Rays Based Tuberculosis Detection Using CNN

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Computer Systems Science & Engineering 2023年第1期44卷 81-97页

作者： Joe Louis Paul Ignatius Sasirekha Selvakumar Kavin Gabriel Joe Louis Paul Aadhithya B.Kailash S.Keertivaas S.A.J.Akarvin Raja Prajan Department of Information Technology Sri Sivasubramaniya Nadar College of EngineeringRajiv Gandhi Salai(OMR)KalavakkamChennai603110Tamil NaduIndia Gullas College of Medicine-University of Visayas BaniladMandaue City6014CebuPhilippines

Tuberculosis(TB)is a severe infection that mostly affects the lungs and kills millions of people’s lives every *** can be diagnosed using chest X-rays(CXR)and data-driven deep learning(DL)*** of its better automated feature extraction capability,convolutional neural net-works(CNNs)trained on natural images are particularly effective in image cate-gorization.A combination of 3001 normal and 3001 TB CXR images was gathered for this study from different accessible public *** different deep CNNs(Resnet50,Resnet101,Resnet152,InceptionV3,VGG16,VGG19,DenseNet121,DenseNet169,DenseNet201,MobileNet)are trained and tested for identifying TB and normal *** study presents a deep CNN approach based on histogram matched CXR images that does not require object segmenta-tion of interest,and this coupled methodology of histogram matching with the CXRs improves the accuracy and detection performance of CNN models for TB ***,this research contains two separate experiments that used CXR images with and without histogram matching to classify TB and non-TB CXRs using deep *** was able to accurately detect TB from CXR images using pre-processing,data augmentation,and deep CNN *** histogram matching the best accuracy,sensitivity,specificity,precision and F1-score in the detection of TB using CXR images among ten models are 99.25%,99.48%,99.52%,99.48%and 99.22%*** histogram matching the best accuracy,sensitivity,specificity,precision and F1-score are 99.58%,99.82%,99.67%,99.65%and 99.56%*** proposed meth-odology,which has cutting-edge performance,will be useful in computer-assisted TB diagnosis and aids in minimizing irregularities in TB detection in developing countries.

关键词： Tuberculosis detection chest x-ray(CXR) convolutional neural networks(CNNs) transfer learning histogram matching

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Efficient Forgery Detection Approaches for Digital Color Images

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Computers, Materials & Continua 2022年第5期71卷 3257-3276页

作者： Amira Baumy Abeer D.Algarni Mahmoud Abdalla Walid El-Shafai Fathi E.Abd El-Samie Naglaa F.Soliman Department of Communications High Institute for Engineering and TechnologyAl-Obour Obour CityEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Department of Electronics and Communications Engineering Faculty of EngineeringZagazig UniversityZagazigSharqia44519Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia

This paper is concerned with a vital topic in image processing:color image forgery detection. The development of computing capabilitieshas led to a breakthrough in hacking and forgery attacks on signal, image,and data communicated over networks. Hence, there is an urgent need fordeveloping efficient image forgery detection algorithms. Two main types offorgery are considered in this paper: splicing and copy-move. Splicing isperformed by inserting a part of an image into another image. On the otherhand, copy-move forgery is performed by copying a part of the image intoanother position in the same image. The proposed approach for splicingdetection is based on the assumption that illumination between the originaland tampered images is different. To detect the difference between the originaland tampered images, the homomorphic transform separates the illuminationcomponent from the reflectance component. The illumination histogramderivative is used for detecting the difference in illumination, and henceforgery detection is accomplished. Prior to performing the forgery detectionprocess, some pre-processing techniques, including histogram equalization,histogram matching, high-pass filtering, homomorphic enhancement, andsingle image super-resolution, are introduced to reinforce the details andchanges between the original and embedded sections. The proposed approachfor copy-move forgery detection is performed with the Speeded Up RobustFeatures (SURF) algorithm, which extracts feature points and feature vectors. Searching for the copied partition is accomplished through matchingwith Euclidian distance and hierarchical clustering. In addition, some preprocessing methods are used with the SURF algorithm, such as histogramequalization and single-mage super-resolution. Simulation results proved thefeasibility and the robustness of the pre-processing step in homomorphicdetection and SURF detection algorithms for splicing and copy-move forgerydetection, respectively.

关键词： Image forgery splicing algorithm copy-move algorithm histogram matching homomorphic enhancement SISR SURF

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Enhanced Destriping of Satellite Data of Ice Surface in Antarctica

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Chinese Journal of Polar Science 2004年第2期15卷 108-117页

作者：鄂栋臣沈强 Chinese Antarctic Center of Surveying and Mapping of Wuhan University Wuhan 430079 China

This paper briefly reviews the cause of the striping and then develops a tapered (Chebwin & Kaiser) window finite impulse response (FIR) filter and a constrained least squares FIR filter by reason of the striping of ASTER satellite data . Both filters minimize the stripes in the visible data and simultaneously minimize any distortion in the filtered data. Finally, the results obtained by using these new filtering methods are quantitatively compared with those produced by other destriping methods.

关键词： advanced spaceborne thermal emission and reflection radiometer (ASTER) destriping fast fourier transform (FFT) finite-impulse response (FIR) lowpass filter histogram matching moment matching.

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Design of UAV Single Object Tracking Algorithm Based on Feature Fusion

Design of UAV Single Object Tracking Algorithm Based on Feat...

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第40届中国控制会议

作者： Changze Li Xiaoxiong Liu Xingwang Zhang Bin Qin Northwestern Polytechnical University

Considering the real-time performance and robustness of the object tracking algorithm,this paper proposes an improved tracking algorithm for single object tracking based on *** algorithm uses Tiny-YOLOv3 for preliminary detection,and the detection results combine histogram of orientation gradient（HOG） and RGB histogram to extract the *** use histogram matching to find the highest similarity between the detected candidate object and the object to be tracked to achieve the purpose of *** tracking strategies are designed when the object is stationary and *** experimental results show that the algorithm improves tracking accuracy and robustness while ensuring real-time tracking.

关键词： Single object tracking Tiny-YOLOv3 HOG histogram matching UAV

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Improved Rotation Invariant Template matching Method Using Relative Orientation Codes

Improved Rotation Invariant Template Matching Method Using R...

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第三十届中国控制会议

作者： LI Zhonghai~1,LIU Chunyu~1,CUI Jianguo~1,SHEN Weifeng~2 1.School of Automation,Shenyang Aerospace University,Shenyang 110136,P.R.China 2.Hanwang Science and Technology Limited Company,Beijing 100080,P.R.China

＜正＞Orientation code is the quantization of pixel gradient orientation,which is illumination invariant,and has become an important template matching *** order to improve accuracy and real time ability,we present conception of relative orientation code,and design template matching method based on relative orientation *** method first selects candidate target points using relative orientation codes histogram matching,then calculate the rotation angle of candidate subimage and rotate the sub image,finally match the relative orientation codes in the sub *** experiment show that this method is robust when the image is rotated by any angle,and the candidate points are selected and matched accurately,and the computing time is less than original method.

关键词： Orientation Code Rotation Invariant Template matching histogram matching

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