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17th IEEE International Symposium on Medical Measurements and Applications (IEEE MeMeA)

作者： Nishitha, R. Amalan, S. Sharma, Shubham Preejith, S. P. Sivaprakasam, Mohanasankar Indian Inst Technol Dept Elect Engn Chennai Tamil Nadu India Indian Inst Technol Healthcare Technol Innovat Ctr Chennai Tamil Nadu India

ISBN: (数字)9781665482998

ISBN: (纸本)9781665482998

It is an arduous task to perform an image Quality Assessment (IQA) for all real-time imaging systems like endoscopy systems which have no reference images for comparison. That being a challenge in itself, the images must be assessed subjectively rather than objectively so that the assessments comply with human perception. imageLab, a complete IQA solution developed in-house has image capture and illumination capabilities integrated with custom test charts and algorithms to provide a detailed analysis for individual image parameters. Though individual parameter analysis is the primary focus of the IQA tool, a technique to provide a score for image quality based on the interdependency of the image parameters is also integrated in the tool. Specifically, the dependency of visual noise and dynamic range on sharpness and resolution has been highlighted in this paper. Eight levels of sharpness were chosen and for every level, image quality in terms of visual noise and dynamic range were computed. The perceived visual noise levels which is part of subjective analysis were factored in the dynamic range calculations and the final image quality score was derived. These detailed measurements would aid in the development of endoscopy systems and the much simpler score-based technique would aid the technicians during maintenance and calibration check before endoscopy examination.

关键词： image Quality Assessment imageLab subjective analysis image parameters score-based technique

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A novel approach to authentication of highbush and lowbush blueberry cultivars using image analysis, traditional machine learning and deep learning algorithms

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EUROPEAN FOOD RESEARCH AND TECHNOLOGY 2025年第2期251卷 193-204页

作者： Ropelewska, Ewa Koniarski, Michal Natl Inst Hort Res Fruit & Vegetable Storage & Proc Dept Konstytucji 3 Maja 1-3 PL-96100 Skierniewice Poland Natl Inst Hort Res Cultivar Testing Nursery & Gene Bank Resources Dep Konstytucji 3 Maja 1-3 PL-96100 Skierniewice Poland

The objective of this study was to classify blueberry cultivars based on image texture parameters using models built using traditional machine learning and deep learning algorithms. The blueberries belonging to highbush cultivars ('Bluecrop', 'Herbert', 'Jersey', and 'Nelson') and lowbush cultivars ('Emil' and 'Putte') were subjected to imaging using a digital camera. The texture parameters from blueberry images in color channels R, G, B, L, a, b, X, Y, Z, U, V, and S were determined. After selection image textures were used to build models for the classification of all highbush and lowbush blueberry cultivars, and highbush blueberry cultivars and lowbush blueberry cultivars, separately. In the case of distinguishing all cultivars, such as 'Bluecrop', 'Herbert', 'Jersey', and 'Nelson', 'Emil' and 'Putte', the classification accuracy reached 92.33% for a model built using a deep learning algorithm. Models built to distinguish only highbush cultivars provided an average accuracy of up to 91.25% (WiSARD). For models developed to classify two lowbush cultivars, an average accuracy reaching 96% (WiSARD) was found. The applied procedure can be used in practice to distinguish blueberry cultivars before their consumption or processing.

关键词： Highbush blueberry Lowbush blueberry image parameters Machine learning models

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An improved background subtraction method for HRI based on image parameters

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KYBERNETES 2014年第7期43卷 1003-1023页

作者： Ma, Qiongxiong Zhang, Tie S China Univ Technol Sch Mech & Automot Engn Guangzhou Guangdong Peoples R China

Purpose - Background subtraction is a particularly popular foreground detection method, whose background model can be updated by using input images. However, foreground object cannot be detected accurately if the background model is broken. In order to improve the performance of foreground detection in human-robot interaction (HRI), the purpose of this paper is to propose a new background subtraction method based on image parameters, which helps to improve the robustness of the existing background subtraction method. Design/methodology/approach - The proposed method evaluates the image and foreground results according to the image parameters representing the change features of the image. It ignores the image that is similar to the first image and the previous image in image sequence, filters the image that may break the background model and detects the abnormal background model. The method also helps to rebuild the background model when the model is broken. Findings - Experimental results of typical interaction scenes validate that the proposed method helps to reduce the broken probability of background model and improve the robustness of background subtraction. Research limitations/implications - Different threshold values of image parameters may affect the results in different environments. Future researches should focus on the automatic selection of parameters' threshold values according to the interaction scene. Practical implications - A useful method for foreground detection in HRI. Originality/value - This paper proposes a method which employs image parameters to improve the robustness of the background subtraction for foreground detection in HRI.

关键词： image processing Robotics Human-robot interaction Background subtraction Foreground detection image parameters

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Note on the Determination of the Offset Lines in Doherty Power Amplifiers

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IEEE MICROWAVE AND WIRELESS COMPONENTS LETTERS 2018年第6期28卷 533-535页

作者： Neveux, Guillaume Rifi, Mohamed Aziz Barataud, Denis Ayad, Mohammed Richard, Elodie Univ Limoges XLIM CNRS UMR 7252 F-87060 Limoges France United Monolith Semicond SAS F-91140 Villebon Sur Yvette France

This letter shows how to find by inspection, the values of the characteristic impedances and the electrical lengths of the offset lines of the main and auxiliary amplifiers constituting a Doherty power amplifier. This letter focuses on the easiest determination of these offset lines using the ABCD matrix coupled with the formalism of image parameters to describe the output matching circuits of the main and auxiliary amplifiers.

关键词： ABCD matrix Doherty image parameters image propagation function impedance matching offset-lines power amplifiers (PAs)

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Unsupervised Optimization for Universal Spatial image Steganalysis

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WIRELESS PERSONAL COMMUNICATIONS 2018年第1期102卷 1-18页

作者： Johnvictor, Anita Christaline Rangaswamy, Ramesh Chidambaram, Gomathy Durgamahanthi, Vaishali SRM Univ Dept ECE Madras Tamil Nadu India Saveetha Engn Coll Dept Elect & Commun Engn Madras Tamil Nadu India

Blind universal steganalysis has been the choice of Steganalysers owing to it's capability to detect stego images without any prior information about the embedding method. Universal steganalysis is a two class optimization problem and the detecting efficiency depends on the feature set chosen from the stego and clean images. Though extracting all possible features of an image may lead to more efficiency the classification suffers due to large dimension of feature set. To overcome the problem of dimensionality appropriate feature reduction techniques need to be employed. This paper presents a blind universal image steganalysis technique that extracts the noise models of adjacent pixels of an image. The exact model construction involves the formation of four dimensional cooccurrence matrices of the quantised and truncated noise residues. From the 106 sub models 34,671 features have been extracted and further reduced by a novel unsupervised optimization technique to identify the most appropriate features for classification. The classifiers implemented include Support Vector Machines (SVM), Multi Layer Perceptron (MLP) and three fusion classifiers based on Bayes, Decision Template and Dempster Schafer fusion schemes. It has been identified that MLP performs better than SVM but is not superior to fusion classifiers. Comparing all the classifiers, Decision Template based fusion method gives the best classification accuracy (99.25%). Thus the proposed unsupervised optimization method combined with Decision Template fusion classification scheme provides the best classification of stego and clear images as compared to the existing research work.

关键词： image steganalysis Ensemble classifiers image parameters Feature set optimization Decision template Multi layer perceptron

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Chlorophyll Content Detection of Field Maize Using RGB-NIR Camera

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IFAC-PapersOnLine 2018年第17期51卷 700-705页

作者： Zhang, Junyi Li, Minzan Sun, Zichun Liu, Haojie Sun, Hong Yang, Wei Key Laboratory of Modern Precision Agriculture System Integration Research Ministry of Education China Agricultural University Beijing100083 China Henan University of Animal Husbandry and Economy Zhengzhou450046 China

In order to rapidly detect the chlorophyll content in the field, the RGB-NIR camera was used to collect the multi-spectral image of maize canopy. The SPAD value was measured at the same time to indicate the chlorophyll content. The multi-spectral images were processed. Considering the features of multi-spectral images, after image median filtering and segmentation to remove the background effect by field soil, dry straw and weeds, 15 image parameters were extracted including the average grey value of each channel (AR, AG, AB and ANIR), the vegetation indices (ANDVI, ANDGI, ARVI, ADVI), vegetation coverage index (VCI), hue average(AH) and image texture parameters (energy (AASM), moment of inertia (ACON), correlation (ACOR), entropy (AEN) and inverse difference moment (AL)). The sensitive parameters were selected by correlation coefficient analysis and RF method. There were 4 and 8 parameters, respectively. After modeling, the LS-SVM model built by RF selected parameters showed better detection accuracy with Rc2=0.87 and Rv2=0.74. It could be used for rapid and non-destructive detection of the chlorophyll content for field maize. © 2018

关键词： image texture Cameras Chlorophyll Forestry image segmentation Infrared devices Inverse problems Median filters Spectroscopy Vegetation Chlorophyll contents image parameters Multispectral images RF method Vegetation index

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BAW Filter Design Method Based on Intrinsically Switchable Ferroelectric BST FBARs

BAW Filter Design Method Based on Intrinsically Switchable F...

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IEEE MTT-S International Microwave Symposium (IMS)

作者： Lee, Seungku Mortazawi, Amir Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48109 USA

ISBN: (纸本)9781509006984

A design method for BAW filters based on intrinsically switchable ferroelectric BST FBARs is presented. A complete set of design equations for ladder-type FBAR filters is derived based on the popular filter synthesis method using image parameters. For the first time, a complete analysis is performed that accurately calculates both the image impedance and propagation constant for BAW filters. Closed-form design equations as a function of FBAR and filter specifications are provided. As an experimental verification, a 1.5-stage switchable ferroelectric BST FBAR filter is designed, fabricated, and measured. When a dc bias is applied, a switchable filter is in its on-state and provides an insertion loss of 5.77 dB with a fractional bandwidth of 1.22% at 1.97 GHz. When in its off-state, the filter exhibits more than 22 dB isolation. Circuit-level simulation results are in very good agreement with the measurement results, validating the proposed BAW filter design method.

关键词： Barium strontium titanate BAW filters bulk acoustic wave FBAR filters film bulk acoustic wave filter synthesis method image parameters

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Uncertainty Aware Site Selection Method for OPC Model Calibration 28

Uncertainty Aware Site Selection Method for OPC Model Calibr...

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Conference on Optical Microlithography XXVIII

作者： Coskun, Tamer H. GLOBALFOUNDRIES Santa Clara CA 95054 USA

ISBN: (纸本)9781628415285

Traditionally, an image parameter metric has been used to analyze the lithography and resist responses versus the test pattern coverage. This metric assumes a variable threshold resist model which is not necessarily the state-of-the art model type used in the latest technology nodes. Additionally, these methods don't consider the statistical nature of the variations where the number of the selected patterns can greatly affect the uncertainty of the model prediction for another set of patterns. We propose a new method that combines the lithography response with uncertainty analysis to select test patterns for OPC model calibration. We also propose a new metric based on resist response to be considered in site selection for advanced resist models. We show that uncertainty aware site selection combined with this new metric gives similar or better model accuracy compared to baseline which requires engineering expertise and other site clustering tools, but with large amount of calibration site reduction. Examples from advanced nodes are given.

关键词： OPC Mode calibration calibration pattern selection image parameters resist-surface parameters resists model model uncertainty

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The feasibility of using image parameters for test pattern selection during OPC model calibration

The feasibility of using image parameters for test pattern s...

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Conference on Optical Microlithography XXIII

作者： Abdo, Amr Viswanathan, Ramya IBM Semicond Res & Dev Ctr SRDC IBM Syst & Technol Grp Hopewell Jct NY 12533 USA

ISBN: (纸本)9780819480545

Model based optical proximity correction (MB-OPC) is essential for the production of advanced integrated circuits (ICs). Calibration of these OPC resist models uses empirical fitting of measured test pattern data. It seems logical that to produce OPC models, acquiring more data will always improve the OPC model accuracy;on the other hand, reducing metrology and model build time is also a critical and continually escalating requirement with the constant increase in the complexity of the IC development process. A trade off must therefore be made to obtain adequate number of data points that produce accurate OPC models without overloading the metrology tools and resources. In this paper, we are examining the feasibility of using the image parameters (IPs) to select the test patterns. The approach is to base our test pattern selection only on the IPs and verify that the resulting OPC model is accurate. Another approach is to reduce the data gradually in different steps using IP considerations and see how the OPC model performance changes. A third, compromise approach is to specify a test pattern set based on IPs and add to that set few patterns based on different considerations. The three approaches and their results are presented in details in this paper.

关键词： Model Based Optical Proximity Correction Model Calibration image parameters Data Collection

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Studies and Evaluation of EIT image Reconstruction in EIDORS with Simulated Boundary Data 2

Studies and Evaluation of EIT Image Reconstruction in EIDORS...

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2nd International Conference on Soft Computing for Problem Solving (SocProS)

作者： Bera, Tushar Kanti Nagaraju, J. Indian Inst Sci Dept Instrumentat & Appl Phys Bangalore 560012 Karnataka India

ISBN: (纸本)9788132216025;9788132216018

Simulated boundary potential data for Electrical Impedance Tomography (EIT) are generated by a MATLAB based EIT data generator and the resistivity reconstruction is evaluated with Electrical Impedance Tomography and Diffuse Optical Tomography Reconstruction Software (EIDORS). Circular domains containing subdomains as inhomogeneity are defined in MATLAB-based EIT data generator and the boundary data are calculated by a constant current simulation with opposite current injection (OCI) method. The resistivity images reconstructed for different boundary data sets and images are analyzed with image parameters to evaluate the reconstruction.

关键词： EIT Simulated boundary data EIDORS image reconstruction Resistivity images image parameters

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