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An Aquatic Organism image Retrieval Hash Algorithm Based on DCT 2

An Aquatic Organism Image Retrieval Hash Algorithm Based on ...

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2nd international conference on Electronic Information Technology and computer Engineering, EITCE 2018

作者： Yu, Yuanhui Deng, Ying Lin, Yanfen Computer Engineering College of JiMei University Xiamen361021 China Xiamen Institute of Technology Xiamen361021 China

In order to overcome the disadvantages of traditional image retrieval algorithms such as inefficiency and time-consuming, an image retrieval algorithm based on DCT Hash is proposed. In this paper, the discrete cosine transform technique is applied to image retrieval. Firstly, the feature hash sequence is generated by computing the DCT transform component of the image based on annular segmentation. Then an image Hash algorithm based on DCT feature Hash sequence is proposed. Experimental results show that the algorithm is robust to image scaling, rotation, noise processing, and has good retrieval performance. © The Authors, published by EDP Sciences, 2018.

关键词： Discrete cosine transforms

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Research on image Segmentation Method Based on Consistency Theorem and Merging Criterion 2

Research on Image Segmentation Method Based on Consistency T...

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2018 2nd international conference on computer Graphics and Digital image processing, CGDIP 2018

作者： Lu, Jia-Min Li, Hao-Fei Yuan, Di Miao, Ya-Wen Lei, Yi-Fan College of Computer and Information Hohai University Nanjing JIANGSU211100 China

This paper takes Hongze lake as an example to explore a novel image segmentation method. We use the regional consistency theorem and the merging criteria to merge discrete pixels of similar features into smaller regions. Thereby, the lake area can be represented by a number of pixels, and the area's change trend can be measured by simply counting the pixel numbers before and after. By using this algorithm, it is possible to skip the cumbersome steps of calculating the area and obtain the area change trends rapidly, as it avoids a large number of duplicate calculations and reduces the situation of missing extreme pixel points. In addition, it saves the required time on manual processing and increases the processing efficiency greatly. Finally, the validity of the proposed algorithm is verified by comparing the lake area data with the yearbook. © Published under licence by IOP Publishing Ltd.

关键词： Pixels

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Moving object detection algorithm using Gaussian mixture model and SIFT keypoint match 2nd

Moving object detection algorithm using Gaussian mixture mod...

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2nd international conference on Machine Learning and Intelligent Communications, MLICOM 2017

作者： Dong, Hang Zhang, Xin College of Electronics and Information Engineering Tongji University Shanghai201804 China

ISBN: (纸本)9783319735634

In the field of image processing, Gaussian mixture model (GMM) is always used to detect and recognize moving objects. Due to the defects of GMM, there are some error detections in the final consequence. In order to eliminate the defects of GMM in moving objects detections, this paper has studied a moving object detection algorithm, combining GMM with scale-invariant feature transform (SIFT) keypoint match. First, GMM is built to obtain the distributions of background image pixels. Then, morphological processing method is applied to improve the quality of binary segmentation image and extract segmentation images of moving objects. Finally, SIFT keypoint match algorithm is used to eliminate misjudgment segmentation images by judging whether the segmentation image matches with the background template or not. Compared with original GMM, the results show that the accuracy of moving object detection has been improved. © ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering 2018.

关键词： image segmentation

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A proposed model for Javanese manuscript images transliteration 2

A proposed model for Javanese manuscript images transliterat...

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2018 2nd international conference on computer Graphics and Digital image processing, CGDIP 2018

作者： Widiarti, A.R. Pulungan, R. Harjoko, A. Marsono Hartati, S. Department of Informatics Engineering Sanata Dharma University Mrican Tromol Pos 29 Yogyakarta Indonesia Department of Computer Science and Electronics Faculty of Mathematics and Natural Sciences Universitas Gadjah Mada Yogyakarta Indonesia Faculty of Cultural Sciences Universitas Gadjah Mada Jalan Sosio Humaniora Bulaksumur Yogyakarta Indonesia

Manuscript transliteration is generally conducted by reading the manuscript and then writing the results to another piece of paper or storing them on a computer using a specific text-processing program. The procedure of transliteration presupposes that the workers fully understand how to read the manuscript, that no consideration is given to the length of the work, and that workers will concentrate sufficiently to minimize errors in rewriting. There are 3 main steps for Javanese manuscript image transliteration, i.e., segmenting manuscript, transliterating of Javanese script letters or numbers, and grouping syllables. The implementation of the proposed model was tested on a Javanese manuscript with catalogue number SB.141 and at a confidence level of 95% and resulting in a success rate between 69.20% and 87.29%. © Published under licence by IOP Publishing Ltd.

关键词： Text processing

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Thresholding Based Soil Feature Extraction from Digital image Samples - A vision Towards Smarter Agrology 2nd

Thresholding Based Soil Feature Extraction from Digital Imag...

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2nd international conference on Information and Communication Technology for Intelligent Systems (ICTIS)

作者： Arunpandian, M. Arunprasath, T. Vishnuvarthanan, G. Rajasekaran, M. Pallikonda Kalasalingam Acad Res & Educ Dept Elect & Commun Engn Virudunagar 626126 Tamil Nadu India

ISBN: (纸本)9783319636733;9783319636726

Soil is one of the natural material, which has the different features for the particular characteristics. In digital image processing is the principle to simplify the identification of soil features. Soil consists of both physical and chemical characteristics. These characteristics are used to find the field of soil usage. Thresholding is the conversion of colour image into binary image and that is used for shape based identification. It applicable for feature extract from curvature, valleys, and non-smoothening surfaces and it enhances the feature and get more information. Fractal dimension is one of the soil feature. A new model is proposed to assign various threshold values apply to the same sample and to determine the range and also the best image model (Red-Green-Blue, Hue-Saturation-Value, Hue-Saturation-Luminance and Hue-Saturation-Intensity) of soil samples. The device can also be modelled as most powerful tool for prediction of land usage for various fields such as agriculture and construction.

关键词： Thresholding Feature extraction Fractal dimension RGB thresholding HSV thresholding HIS thresholding HSL thresholding

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Contourlet based image denoising method combined recursive cycle-spinning algorithm 2nd

Contourlet based image denoising method combined recursive c...

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2nd international conference on Machine Learning and Intelligent Communications, MLICOM 2017

作者： Fan, Hongda Xie, Xufen Zhang, Yuncui Zou, Nianyu Research Institute of Photonics Dalian Polytechnic University No. 1 Qinggongyuan Ganjingzi District Dalian116034 China

ISBN: (纸本)9783319735634

Contourlet transform lacks shift invariance, and threshold processing on the coefficients may produce pseudo Gibbs phenomena. For recursive cycle spinning algorithm can reduce the pseudo Gibbs phenomena. This paper studies the image denoising method combined with Contourlet transform and recursive cycles pinning algorithm, The analysis show that the factor need to be adjusted. When the adjustment factor takes best value, the corresponding image objective index PSNR (Peak Signal to Noise Ratio) is the largest, and images visual effects are optimal. The experimental results show that: compared with original algorithm, changing adjustment factor, the PSNR of denoised image can be improved 0.6–1.2. © ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering 2018.

关键词： image denoising

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vision-based target tracking intelligent robot using NI myRIO with LabVIEW 1

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2nd international conference on Intelligent Computing and Communication, ICICC 2017

作者： Gade, Anita Angal, Yogesh Department of E&TC Engineering JSPM’s Bhivarabai Sawant Institute of Technology & Research SPPU Pune India

ISBN: (数字)9789811072451

ISBN: (纸本)9789811072444

Robots are worked to do tasks that are risky to people, for example, defusing bombs and discovering survivors in unsteady environments and investigation. The rising exploration field on scaled-down programmed target following robot is given significance in hazardous, military and industrial areas for navigation, observation, safety, and goal acknowledgment by image processing. The real-time vision-based technique is used for target tracking. The objective of this system is to develop the proto robot capable of following a target using image processing. Normally, the way of a mobile robot is controlled by a pre-identified data about objects in nature. In this developed system, the robot tracks the desired destination goal in a systemized way. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Target tracking

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Calcification detection using deep structured learning in intravascular ultrasound image for coronary artery disease 2

Calcification detection using deep structured learning in in...

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2nd international conference on BioSignal Analysis, processing and Systems, ICBAPS 2018

作者： Sofian, Hannah Chia Ming, Joel Than Mohamad, Suraya Noor, Norliza Mohd Universiti Teknologi Razak School of UTM in Engineering and Advanced Technology Malaysia Institute of Information Technology Kuala Lumpur Malaysia Universiti Kuala Lumpur British Malaysian Institute Kuala Lumpur Malaysia

ISBN: (纸本)9781538612774

Coronary artery disease (CAD) is also known as atherosclerosis, a non-communicable disease (NCD) in cardiovascular disease (CVD). The plaques and the calcification embedded in the coronary artery inner wall make the blood vessel area narrow. The standard practice by the radiologists and medical clinical are by visual inspection to detect calcification on the intravascular ultrasound (IVUS) image. In this study, we focus on detecting the calcification present and calcification absent in the coronary artery disease for catheter frequency 20MHz IVUS image using Directed Acyclic Graph (DAG) network. The four types images that are Cartesian coordinate image, polar reconstructed coordinate image, Cartesian coordinate warp image with and polar constructed warp image of were used as an input image in this study. The convolutional neural network (CNN) using Directed Acyclic Graph network (ResNet101) together with the three types classifier (Decision Tree, K-nearest Neighbour and Naïve Bayesian) were investigated for the detection of the calcification present and calcification absent. In this work, we used dataset B from MICCAI Challenge 2011 that consists of 2175 coronary artery disease IVUS image where 530 of the images with calcification and 1645 are without calcification to demonstrate our framework. The performance measures such as the accuracy, sensitivity, specificity, positive prediction value and negative prediction value were evaluated and compared with the ground truth provided. The ResNet101 architecture, the four types of images and the three types of the classifier gave good accuracy. © 2018 IEEE.

关键词： Bone

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Research on Rapid Reconstruction of Three-dimensional Model in Medical image processing Based on VTK Library

Research on Rapid Reconstruction of Three-dimensional Model ...

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2019 2nd international conference on computer Science and Advanced Materials(CSAM 2019)

作者： Li Qiong Gan Yongjin Ning Weilian Yulin Normal University

Medical image three-dimensional model reconstruction technology, which uses two-dimensional medical image sequence to reconstruct three-dimensional model, provides doctors with intuitive, comprehensive and accurate information of lesions and normal tissues, is one of the hotspots in the field of medical imaging. According to different reconstruction models, virtual arbitrary cutting is realized, and surface cutting and volume cutting, and the interactive method of virtual cutting is discussed. The minimum error in merging is calculated to determine the location of the new vertex. Using the toolkit and library to develop a medical image 3D model reconstruction and visualization system, can read medical image data in a specific format, perform 3D model reconstruction, and finally real-time interaction. The experimental results show that the proposed method can effectively preserve the graphical features of the original model and provide convenient use for real-time rendering. The VTK toolkit and library developed a medical image 3D model reconstruction and visualization system that can read medical image data in a specific format, perform 3D model reconstruction, and ultimately real-time interaction.

关键词： VTK Medical image Three-dimensional model

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A Review on computer-Aided Modelling and Quantification of PET-CT images for Accurate Segmentation to Bring Imagination to Life 1

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2nd international conference on Intelligent Communication, Control and Devices (ICICCD)

作者： Shaik, Ziaur Rahiman Kumar, Ch. Sumanth KLM Coll Engn Dept ECE Kadapa 516003 Andhra Pradesh India GITAM Univ Sch Technol Dept ECE Bengaluru 562163 Karnataka India

ISBN: (数字)9789811059032

ISBN: (纸本)9789811059032;9789811059025

image segmentation is a process of dividing image into smaller parts to identify the individual objects. Often, this process helps in the quantification of digital images related to disease complications for metabolic process. This work reports on the use of computer-aided modelling tools and rapid prototyping technology to document, preserve and reproduce in three dimensions, and historic machines and mechanisms are used for accurate medical diagnosis. Epidemiological and clinical trials have confirmed the greater incidence and prevalence of deaths due to the inability to acquire qualitative information from the acquisition of images in primary stage itself. Rapid prototyping gives a better understanding of clinical and physiologic mechanisms of various disorders and pain, lesion detection. In image segmentation process, thresholding method is suitable for defining optimal value for identification and detection of region of interest. The standard uptake value (SUV) is based on selecting threshold value to utilize a similarity metric between the grey level of image and data points obtained from the threshold values. This is based on the intensities or inhomogeneity of clustering framework. Affinity propagation is used for images as a matrix by measuring the square patches from similarity texture. A major challenge in computer vision is to extract this information directly from the images available to us, help users, and to see and feel as an actual part in order to bring a computer image to life. Actually, the framework is given by PET-CT images which is used to identify and detect malignant tissues in a human body with accurate measurements of SUVs. This process involves ROI identification, segmentation, rendering and SUV functional quantification for promising results. The results obtained from computer modelling are transformed into real substance by rapid prototyping technology to feel and provide accurate diagnosis to patient.

关键词： Quantification SUV Epidemiological Rapid prototyping

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