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Non-ideal iris segmentation using Polar Spline RANSAC and illumination compensation

COMPUTER vISION AND image UNDERSTANDING 2019年 188卷 102787-000页

作者： Labati, Ruggero Donida Munoz, Enrique Piuri, vincenzo Ross, Arun Scotti, Fabio Univ Milan Dept Comp Sci Via Bramante 65 I-26013 Crema CR Italy Michigan State Univ Dept Comp Sci & Engn E Lansing MI 48824 USA

In this work, we propose a robust iris segmentation method for non-ideal ocular images, referred to as Polar Spline RANSAC, which approximates the iris shape as a closed curve with arbitrary degrees of freedom. The method is robust to several nonidealities, such as poor contrast, occlusions, gaze deviations, pupil dilation, motion blur, poor focus, frame interlacing, differences in image resolution, specular reflections, and shadows. Unlike most techniques in the literature, the proposed method obtains good performance in harsh conditions with different imaging wavelengths and datasets. We also investigate the role of different illumination compensation techniques on the iris segmentation process. The experiments showed that the proposed method results in higher or comparable accuracy with respect to other competing techniques presented in the literature for images acquired in non-ideal conditions. Furthermore, the proposed segmentation method is generalizable and can achieve competitive performance with different state-of-the-art feature extraction and matching techniques. In particular, in conjunction with a well-known recognition schema, it achieved Equal Error Rate of 4.34% on DB WvU, Equal Error Rate of 5.98% on DB QFIRE, and pixel-wise classification error rate of 0.0165 on DB UBIRIS v2. Moreover, experiments using different illumination compensation techniques demonstrate that algorithms based on the Retinex model offer improved segmentation and recognition accuracy, thereby highlighting the importance of adopting illumination models for processing non-ideal ocular images.

关键词： image resolution

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Multithreaded image processing using ReconOS on reconfigurable computing system 1

Multithreaded image processing using ReconOS on reconfigurab...

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1st International Conference on Emerging Trends and Innovations In Engineering And Technological Research, ICETIETR 2018

作者： Sanal, Syam Engineer, Pinalkumar J. Electronics Engineering Department S.V. National Institute of Technology Surat India

ISBN: (纸本)9781538657447

This paper presents the implementation of Particle filter based Object tracking using ReconOS on Reconfigurable Computing System. Multithreading can be used to improve the performance of complex image processing algorithms, but their sequential execution is a barrier which can be tackled by the effective use of FPGAs. In order to accomplish the desired performance, an operating system, ReconOS is used on an ARM based CPU-FPGA hybrid platform. ReconOS extends communication and synchronization primitives of operating systems like mutexes, semaphores, condition variable and message boxes to reconfigurable hardware. ReconOS provides the advantage of mapping the particle filter algorithm into reconfigurable hardware and accessing the data from software threads. Thus providing improved performance, portability and unified appearance as well as transparency to the object tracking application. © 2018 IEEE.

关键词： Field programmable gate arrays (FPGA)

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A flexible system for gesture based human-robot interaction 51

A flexible system for gesture based human-robot interaction

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51st CIRP Conference on Manufacturing systems (CIRP CMS)

作者： Tellaeche, Alberto Kildal, Johan Maurtua, Inaki IK4 Tekniker Calle Inaki Goenaga 5 Eibar Gipuzkoa Spain

In industrial collaborative robotics, operators and robots perform complex tasks working together without physical barriers. Under this premise, the availability of a flexible, robust and fast interaction system between the robot and the workers is a necessity. Human beings use voice and gestures to achieve a natural interaction. Taking into account the environmental conditions usually present in workshops with noise and poor lighting conditions, combining both communication channels can contribute to make the interaction more robust. This research work presents a solution to define, setup and run a flexible and robust gesture interaction system to integrate in collaborative robotics applications. (C) 2018 The Authors. Published by Elsevier B.v. Peer-review under responsibility of the scientific committee of the 51st CIRP Conference on Manufacturing systems.

关键词： Robust gesture detection Human-Robot collaboration image processing machine learning algorithms

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DEEP NEURAL NETWORKS FOR NON-LINEAR MODEL-BASED ULTRASOUND RECONSTRUCTION

DEEP NEURAL NETWORKS FOR NON-LINEAR MODEL-BASED ULTRASOUND R...

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IEEE Global Conference on Signal and Information processing (GlobalSIP)

作者： Almansouri, H. venkatakrishnan, S. v. Buzzard, G. T. Bouman, C. A. Santos-villalobos, H. Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA Oak Ridge Natl Lab Imaging Signals & Machine Learning Grp Oak Ridge TN 37831 USA Purdue Univ Dept Math W Lafayette IN 47907 USA

ISBN: (纸本)9781728112954

Ultrasound reflection tomography is widely used to image large complex specimens that are only accessible from a single side, such as well systems and nuclear power plant containment walls. Typical methods for inverting the measurement rely on delay-and-sum algorithms that rapidly produce reconstructions but with significant artifacts. Recently, model-based reconstruction approaches using a linear forward model have been shown to significantly improve image quality compared to the conventional approach. However, even these techniques result in artifacts for complex objects because of the inherent non-linearity of the ultrasound forward model. In this paper, we propose a non-iterative model-based reconstruction method for inverting measurements that are based on non-linear forward models for ultrasound imaging. Our approach involves obtaining an approximate estimate of the reconstruction using a simple linear back-projection and training a deep neural network to refine this to the actual reconstruction. We apply our method to simulated and experimental ultrasound data to demonstrate dramatic improvements in image quality compared to the delay-and-sum approach and the linear model-based reconstruction approach.

关键词： image reconstruction Ultrasonic imaging Mathematical model Training Neural networks Imaging Transducers

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Combined local and global image enhancement algorithm 16

Combined local and global image enhancement algorithm

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16th image processing: algorithms and systems Symposium 2018

作者： voronin, v. Semenishchev, E. Ponomarenko, M. Agaian, S. Don State Technical University Dept. of Radio-Electronics Systems Gagarina 1 Rostov on Don Russia Tampere University of Technology Tampere Finland CUNY College of Staten Island Dept. of Computer Science New YorkNY United States

We present a new image enhancement algorithm based on combined local and global image processing. The basic idea is to apply α-rooting image enhancement approach for different image blocks. For this purpose, we split image in moving windows on disjoint blocks with different size (8 by 8, 16 by 16, 32 by 32 and, i.e.). The parameter alfa for every block driven through optimization of measure of enhancement (EME). The resulting image is a weighted mean of all processing blocks. This strategy for image enhancement allows getting more contrast image with the following properties: irregular lighting and brightness gradient. Some experimental results are presented to illustrate the performance of the proposed algorithm. © 2018 Society for Imaging Science and Technology.

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Features of the diagnostic information processing for congenital lung malformations in newborns for the automated analysis and surgical navigation systems 22

Features of the diagnostic information processing for congen...

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22nd International Conference on Knowledge-Based and Intelligent Information and Engineering systems (KES)

作者： Nemkovskiy, G. B. Dorofeeva, E., I Tumanova, U. N. Degtyarev, D. N. Kozlova, A., v Prohin, A., v Minist Healthcare Russian Federat Fed State Budget Inst Natl Med Res Ctr Obstet Gynecol & Perinatol Oparina 4 Moscow 117198 Russia WESTTRADE LTD 1st Warshvsky Prd1A Bl 9 Moscow 115201 Russia

The article describes the processes of collecting and adapting the diagnostic information necessary for use in automated analysis of three-dimensional images and surgical navigation. The work is carried out on the basis of the NMRC Obstetrics, Gynecology And Perinatology named after v.I. Kulakov of the Ministry of Health of the Russian Federation with the fmancial support of the Ministry of Science and Education of the Russian Federation (Agreement dated 03.10.2016 No. 14.607.21.0162, unique identifier REMEF160716X0162) The work is devoted to the features of collection, segmentation and description of the results of preoperative radiological diagnostics of newborn patients with congenital malformations of the lungs, such as bronchopulmonary sequestration (BS) and congenital cystic adenomatous malformation (CCAM). The goal of the work is the development of standards for the collection, classification and segmentation of various diagnostic information of congenital lung malformations in newborns necessary to use in automated three-dimensional image analysis and surgical navigation. In order to expand the scope of application, it was decided to supplement the data bank with information from the patient's phenotypic chart, compiled by the clinical geneticist when examining the patient. According to the developed and implemented algorithms we collected and segmented 924 series of images belonging to 148 patients with lung anomalies and 356 series of normal lung. Available text descriptions of the series are reconstructed to the original developed standard. At present, using this data bank, a subsystem of neural network analysis and reconstruction of diagnostic images of newborn patients is being developed, as well as a surgical navigation system for performing endoscopic surgical manipulations on patients for congenital malformations of the lungs. (C) 2018 The Authors. Published by Elsevier Ltd.

关键词： neonathology surgical navigation medical imaging neural networking image analysis congenital malformations congenital lung malformations

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Long Term Safety Area Tracking (LT-SAT) with online failure detection and recovery for robotic minimally invasive surgery

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MEDICAL image ANALYSIS 2018年 45卷 13-23页

作者： Penza, veronica Du, Xiaofei Stoyanov, Danail Forgione, Antonello Mattos, Leonardo S. De Momi, Elena Politecn Milan Dept Elect Informat & Bioengn Pzza L Da Vinci 32 I-20133 Milan Italy Ist Italiano Tecnol Dept Adv Robot Via Morego 30 I-16163 Genoa Italy UCL Ctr Med Image Comp Dept Comp Sci London England Osped Niguarda Ca Granda Pzza Osped Maggiore 3 I-20162 Milan Italy

Despite the benefits introduced by robotic systems in abdominal Minimally Invasive Surgery (MIS), major complications can still affect the outcome of the procedure, such as intra-operative bleeding. One of the causes is attributed to accidental damages to arteries or veins by the surgical tools, and some of the possible risk factors are related to the lack of sub-surface visibilty. Assistive tools guiding the surgical gestures to prevent these kind of injuries would represent a relevant step towards safer clinical procedures. However, it is still challenging to develop computer vision systems able to fulfill the main requirements: (i) long term robustness, (ii) adaptation to environment/object variation and (iii) real time processing. The purpose of this paper is to develop computer vision algorithms to robustly track soft tissue areas (Safety Area, SA), defined intra-operatively by the surgeon based on the real-time endoscopic images, or registered from a pre-operative surgical plan. We propose a framework to combine an optical flow algorithm with a tracking-by-detection approach in order to be robust against failures caused by: (i) partial occlusion, (ii) total occlusion, (iii) SA out of the field of view, (iv) deformation, (v) illumination changes, (vi) abrupt camera motion, (vii), blur and (viii) smoke. A Bayesian inference-based approach is used to detect the failure of the tracker, based on online context information. A Model Update Strategy (MUpS) is also proposed to improve the SA re-detection after failures, taking into account the changes of appearance of the SA model due to contact with instruments or image noise. The performance of the algorithm was assessed on two datasets, representing ex-vivo organs and in-vivo surgical scenarios. Results show that the proposed framework, enhanced with MUpS, is capable of maintain high tracking performance for extended periods of time (similar or equal to 4 min - containing the aforementioned events) with high precisi

关键词： Long-term tissue tracking Tracking failure detection Model Update Strategy Robotic minimally invasive surgery

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A Finger-vein Biometric System Based on Textural Features

A Finger-vein Biometric System Based on Textural Features

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International Conference on Information Technology and systems (ICITS)

作者： Carrera, Enrique v. Izurieta, Santiago Carrera, Ricardo Univ Fuerzas Armadas ESPE Dept Elect & Elect Sangolqui 171103 Ecuador Univ San Francisco Quito Colegio Ciencias & Ingn Cumbaya 170901 Ecuador

ISBN: (纸本)9783319734507;9783319734491

Biometric systems are being widely used today for automated authentication purposes. In particular, vascular biometrics or vein recognition is receiving a large amount of attention because of its several advantages related to security and convenience. However, images containing vein patterns normally include more information than just those structural arrangements. Thus, we propose a finger-vein biometric system based exclusively on textural features to evaluate the usefulness of the remaining information around vein patters. Textural features are obtained through gray-level co-occurrence matrices from the wavelet detail coefficients belonging to finger-vein images. The evaluation of the proposed biometric system is based on a standardized finger-vein database and its results show favorable improvements on the finger-vein authentication accuracy when textural features are incorporated in the biometric process.

关键词： Finger-vein biometry Digital image processing Machine learning algorithms

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Dynamic approach for lane detection using google street view and CNN

arXiv

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arXiv 2019年

作者： Mamidala, Rama Sai Uthkota, Uday Joseph Antony, A. Shankar, Mahamkali Bhavani Narasimhadhan, A.v. National Institute of Technology Surathkal Mangalore India Insight Centre for Data Analytics Dublin City University Dublin Ireland

Lane detection algorithms have been the key enablers for a fully-assistive and autonomous navigation systems. In this paper, a novel and pragmatic approach for lane detection is proposed using a convolutional neural network (CNN) model based on SegNet encoder-decoder architecture. The encoder block renders low-resolution feature maps of the input and the decoder block provides pixel-wise classification from the feature maps. The proposed model has been trained over 2000 image data-set and tested against their corresponding ground-truth provided in the data-set for evaluation. To enable real-time navigation, we extend our model's predictions interfacing it with the existing Google APIs evaluating the metrics of the model tuning the hyper-parameters. The novelty of this approach lies in the integration of existing segnet architecture with google APIs. This interface makes it handy for assistive robotic systems. The observed results show that the proposed method is robust under challenging occlusion conditions due to pre-processing involved and gives superior performance when compared to the existing methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Pixels

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A fast, block based, copy-move forgery detection approach using image gradient and modified K-means 3rd

A fast, block based, copy-move forgery detection approach us...

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3rd International Symposium on Intelligent systems Technologies and Applications, ISTA 2017

作者： Hajihashemi, v. Gharahbagh, A. Alavi Software Department Bam Pardazesh Tehran Co. Tehran Iran Department of Electrical and Computer Engineering Islamic Azad University Shahrood Branch Shahrood Iran

ISBN: (纸本)9783319683843

In recent years, due to the fast development of digital images, a rapid growth of research interest in the forgery detection in digital images has been happened. One of the most common techniques in creating forged images is copy-move (region duplication) technique. In this paper, a new method for copy-move forgery detection in digital images is proposed. In this paper a region duplication detection technique which utilizes the image gradient is proposed. In the proposed approach, first the gradient of image is divided into overlapped blocks. Using gradient versus other techniques, decreases processing time in feature extraction step. A fast pre clustering algorithm is another added step to speedup method by dividing search area into some subset. The unknown parameters of proposed method are determined by implementing different conditions on two standard databases. Finally, the performance of the proposed method is compared with some state of art methods and the acceptable accuracy and lower run time of it, is verified. © Springer International Publishing AG 2018.

关键词： Clustering algorithms

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