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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems XI"

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Hybrid Detector with Interpixel Communication for Color X-ray Imaging

Hybrid Detector with Interpixel Communication for Color X-ra...

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IEEE International conference on Electronics, Circuits and systems (ICECS)

作者： P. Grybos R. Kleczek P. Kmon A. Krzyzanowska P. Otfinowski R. Szczygiel M. Zoladz AGH University of Science and Technology Krakow Poland

This paper presents a readout integrated circuit of pixel architecture called MPIX (Multithreshold PIXels), designed for CdTe pixel detectors used in high-energy X-ray imaging applications. The MPIX IC of the area of $9.6\ \text{mm} \times 20.3\ \text{mm}$ is designed in a CMOS 130 nm process. The IC core is a matrix of $96\times 192$ square-shaped pixels of $100\ \mu \mathrm{m}$ pitch. Each pixel contains an analog front-end, four independently working discriminators, and four 12-bit ripple counters. Such pixel architecture allows photon processing one by one and selecting the X-ray photons according to their energy (X-ray color imaging). The MPIX chips are bump-bonded to pixel CdTe sensor with a pitch of $100\ \mu \mathrm{m}$ and thickness of $750\ \mu \mathrm{m}$ . These hybrid detectors (sensor bump-bonded to readout integrated circuit) are characterized by test pulses and X-ray radiation. To match the different range of applications the MPIX chip has 8 possible different gain settings. In the high gain mode, the chip can operate with Xray photons up to 46 keV and has the Equivalent Noise Charge (ENC) of 123 el. rms. In the low gain mode, the ENC is equal to 192 el. rms, and the chip can process the X-ray photons of energy up to 154 keV. The matrix of 18432 pixels has a very good uniformity: globally set threshold has an effective pixel to pixel offset spread of 1 mV (for the full threshold range up to 800 mV). The power consumption per pixel is $80\ \mu \mathrm{W}/\text{pixel}$ . Additionally, to deal with charge sharing effects in a thick semiconductor pixel sensor, Multithreshold Pattern Recognition algorithms are implemented in the MPIX IC.

关键词： Integrated circuits Power demand II-VI semiconductor materials image color analysis Radiation detectors Detectors Pattern recognition

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Significant Target Detection of Traffic Signs Based on Walsh-Hadamard Transform

Significant Target Detection of Traffic Signs Based on Walsh...

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Computing conference, 2019

作者： Yang, xi Quan Sun, Ying College of Information Sciences and Technology Northeast Normal University Changchun China

ISBN: (纸本)9783030228705

This paper proposes a method based on Walsh-Hadamard transform to detect the significant target of traffic signs. This method uses the Walsh-Hadamard transform and normalized image binary spectrum to detect the traffic target with significant target. Experiments show that the algorithm is shorter than other algorithms and can quickly and effectively detect the significant area of traffic signs compared with other algorithms in the text. © 2019, Springer Nature Switzerland AG.

关键词： Traffic signs

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Rocket Rolling Attitude Determining Method Based on Optical Tracking Measurement 2

Rocket Rolling Attitude Determining Method Based on Optical ...

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2019 2nd International conference on Advanced algorithms and Control Engineering, ICAACE 2019

作者： Shuhua, Cui Tiening, Nie Guo, Li Yonghua, Li State Key Laboratory of Astronautic Dynamics Xi'an710043 China Xi'An Satellite Control Center Xi'an710043 China

The rocket attitude is used to describe the attitude and state of the carrier rocket moving around its mass center and is also an important parameter used to evaluate the stability of the rocket movement. Aimed at the problem that it is difficult to determine the optical tracking measurement-based rocket rolling attitude, special positions in the rocket video image are selected skillfully to perform the measurement interpretation, establish corresponding rolling attitude calculation model, model and analyze the carrier rolling attitude changes caused by the measurement interpretation error. This method not only expands the data processing method used to select the rolling attitude measurement for interpretation, but also provides effective judging basis for analyzing, evaluating and improving the rocket performance. © Published under licence by IOP Publishing Ltd.

关键词： Rockets

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A Preliminary Evaluation of a Basic Fluorescence image processing in MentorEye System Using Artificially Prepared Phantoms 6th

A Preliminary Evaluation of a Basic Fluorescence Image Proce...

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6th International conference on Information Technology in Biomedicine (ITIB)

作者： Majak, Marcin Wojtkow, Magdalena Zmudzinska, Matylda Macherzynski, Wojciech Kulas, Zbigniew Popek, Michal Swiatek-Najwer, Ewelina Zuk, Magdalena Wroclaw Univ Sci & Technol Wroclaw Poland

ISBN: (纸本)9783319912110

This paper presents preliminary results for fluorescence image processing implemented in MentorEye computer-aided surgery system. For this purpose we have prepared some artificial phantoms enabling fluorescence excitation with different properties. In this study, we have used basic algorithms for image segmentation with some modifications for noise removal and transparency mask generation. MentorEye system comprises of few modules for planning, virtual plan realization and finally validation phase. Apart from well-known CT DICOM data, we have enriched intraoperative module with a fluorescence visualization. MentorEye uses near-infrared (NIR) fluorescent light for better tumor identification inside operating room.

关键词： image segmentation Fluorescence imaging Computer-aided surgery

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Colour image Denoising using Curvelets and Scale Dependent Shrinkage

Colour Image Denoising using Curvelets and Scale Dependent S...

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IEEE International conference on systems, Man and Cybernetics

作者： Oussama Kadri Zine-Eddine Baarir Gerald Schaefer Iakov Korovin Mohammed Khider University Biskra Algeria Loughborough University Loughborough U.K. Southern Federal University Taganrog Russia

ISBN: (数字)9781728185262

ISBN: (纸本)9781728185279

With the widespread use of image processing and computer vision applications, effective denoising methods are highly sought after, prompting the development of a variety of algorithms under different assumptions on noise and signal properties. However, most of these techniques are developed to deal with grayscale images, and are typically extended to colour images by processing each RGB channel separately. In this paper, we extend the curvelet power shrinkage algorithm, introduced previously for grayscale images, to colour image denoising, by applying the proposed method in the luminance/opponent-colour YCbCr colour space to take into consideration image inter-channel dependencies. The performance of the proposed algorithm on colour images corrupted by additive white Gaussian noise is evaluated in terms of both objective and subjective measures, and the obtained results show our method to be competitive to other methods including curvelet domain hard thresholding and MSt-SVD.

关键词： image quality image color analysis image edge detection Noise reduction Gray-scale image denoising Noise level

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Implementation-aware design of image-based control with on-line measurable variable-delay 22

Implementation-aware design of image-based control with on-l...

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22nd Design, Automation and Test in Europe conference and Exhibition (DATE)

作者： Medina, Robinson Stuijk, Sander Goswami, Dip Basten, Twan Eindhoven Univ Technol Dept Elect Engn Eindhoven Netherlands TNO ESI Eindhoven Netherlands TNO Powertrains Dept Helmond Netherlands

ISBN: (纸本)9783981926323

image-based control uses image-processing algorithms to acquire sensing information. The sensing delay associated with the image-processing algorithm is typically platform-dependent and time-varying. Modern embedded platforms allow to characterize the sensing delay at design-time obtaining a delay histogram, and at run-time measuring its precise value. We exploit this knowledge to design variable-delay controllers. This design also takes into account the resource configuration of the image processing algorithm: sequential (with one processing resource) or pipelined (with multiprocessing capabilities). Since the control performance strongly depends on the model quality, we present a simulation benchmark that uses the model uncertainty and the delay histogram to obtain bounds on control performance. Our benchmark is used to select a variable-delay controller and a resource configuration that outperform a constant worst-case delay controller.

关键词： Delays Sensors Task analysis Histograms Predictive models Benchmark testing Uncertainty

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An Algorithm for Exact Retinal Vein Extraction 18th

An Algorithm for Exact Retinal Vein Extraction

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18th International conference on Computer Information systems and Industrial Management

作者： Szymkowski, Maciej Najda, Dawid Saeed, Khalid Bialystok Tech Univ Fac Comp Sci Bialystok Poland

ISBN: (纸本)9783030289560;9783030289577

Recently more interest in retina-based human recognition is observable. It is connected with the fact that this biometrics trait can guarantee absolute certainty in the case of human identity. In the literature, one can easily observe that most of the algorithms are based on veins system and its pattern. A method to extract recently mentioned structure is presented in this paper. The proposed approach consists of three main parts: preprocessing, segmentation and unnecessary artifacts removal. During the research, the authors used different image processing methods for veins system extraction, especially diversified binarization algorithms and edge detection approaches were tested. In the time of the experiments the authors took into consideration not only accuracy but also proposed solution efficiency. Performed tests have shown that it is clearly possible to extract veins system with satisfactory precision and efficiency.

关键词： Biometrics Retina color images Segmentation Retinal veins image processing

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Channel based Threshold Segmentation of Multi-Class Cervical Cancer using Mean and Standard Deviation on Pap Smear images

Channel based Threshold Segmentation of Multi-Class Cervical...

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Electronics and Sustainable Communication systems (ICESC), 2020 International conference on

作者： S. Jaya M. Latha Sri Sarada College for Women Salem India

ISBN: (数字)9781728141084

ISBN: (纸本)9781728141091

Cervical cancer is the second most dangerous metastatic tumor where grows in a woman's cervix. Pap smear is the simplest screening test for the detection of cancer at the starting stage. Cervical cancer has two types of Normality and abnormality cancer which contains the cell and cytoplasm in the same structure. It is difficult to identify a cancerous nucleus in the cell. In image processing, various algorithms are used to segment the nucleus alone in microscopic images. The primary scope of this paper is focusing on Pre-processing, Segmentation and Feature Extraction with six levels of Pap images. The performance evaluation has been calculated based on the segmentation results. In the first phase, pre-processing used mean filters to remove noise and enhanced with CLAHE. In the second phase, Segmentation used threshold value by taking the sum of three channels with the proposed methodology in mean and standard deviation. In the third phase, Properties of image regions, Shapes, Textures and some statistical features are extracted after segmentation. To evaluate performance measure used SSIM for each type of cancerous segmentation that is compared with K-means and Fuzzy C-means algorithm. Thus, the proposed work of separation and addition of RGB channel based segmentation gives the best results for nucleus segmentation in Pap smear images. The accuracy level 94.60 % has been obtained by using SVM and KNN classification for 182 Pap smear images with a class of six labels. Matlab R2016a is used as a programming tool.

关键词： image segmentation Feature extraction Cervical cancer Classification algorithms Clustering algorithms Standards

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Summary of Leaf-based plant disease detection systems: A compilation of systematic study findings to classify the leaf disease classification schemes

Summary of Leaf-based plant disease detection systems: A com...

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World conference on Smart Trends in systems, Security and Sustainability (WorldS4)

作者： Ravindra Jogekar Nandita Tiwari RKDF Institute of Science and Technology Sarvepalli RadhaKrishnan University Bhopal MP India

ISBN: (数字)9781728168234

ISBN: (纸本)9781728168241

Food production is the mainstay of every economy, and relies on the yield of the agricultural producers. This yield is often affected by micro and macro diseases that occur throughout a given fruit-bearing plant's growth. For example, some of the diseases affecting banana leaf include Fusarium oxysporum, Mycosphaerella musicola, Gloeosporium musae, Erwinia Carotovora, Pseudomonas Solanaceanim, Pentalonia nigronervosa, Erionota thrax, BSV and BBM Virus. Such pathogens are countless, so advances in image processing are deemed necessary to categorize and suggest remedial measures for those viruses. A sizeable proportion of work conducted in the area aims at linear approaches where classification, attribute extraction, and definition are conducted to detect aesthetically detectable ailments. However, these interventions are not equipped for bigger and more diverse sets of data, so machine learning and artificial intelligence-based approaches such as Q-learning, re-enforcement learning, etc. take responsibility for formulating diseases which were invisible to the human eye in every component of the processing layers. Because of such a wide variety of diseases and such a large number of processing algorithms, system designers are often misleading as to which algorithms combination should be used to classify which kind of diseases. To eliminate this confusion, this paper compare and objectively evaluate some of the latest existing techniques in this field, and evaluate the best fusion of algorithms that can be used to develop a highly accurate classification system for leaf disease. This finding suggests plenty more research directions which must be undertaken to enhance system efficiency.

关键词： Diseases Feature extraction Classification algorithms Support vector machines Training Testing image segmentation

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image De-Raining for Driver Assistance systems using U-Net based GAN

Image De-Raining for Driver Assistance Systems using U-Net b...

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2019 IEEE International conference on Signal processing, Information, Communication and systems, SPICSCON 2019

作者： Ramwala, Ojas A. Paunwala, Chirag N. Paunwala, Mita C. Electronics Engineering SVNIT Surat India E C Engineering SCET Surat India

ISBN: (纸本)9781728142944

The visual appeal of images gets deteriorated when captured under unfavorable weather conditions thus rendering them unsuitable for optimum performance on vision-based systems. Performance of Driver Assistance systems (DAS) depends on the quality of the images fed to the computer vision algorithms. This paper attempts to leverage generative modelling capabilities of Generative Adversarial Networks by utilizing special architectures for generator and discriminator. The loss function utilized is the efficient pixel mean square loss. Discriminator used here is a standard binary cross-entropy classifier intended to classify whether the predicted de-rained image of the generator matches the real high-resolution image or not. The generator network is a Fully Convolutional U-Net architecture. Experiments indicate that the proposed architecture produces de-rained images indistinguishable from their clean images using only 30 epochs and performs better than various novel approaches. © 2019 IEEE.

关键词： Generative adversarial networks

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