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Edge detection based on Retinex theory and wavelet multiscale product for mine images

APPLIED OPTICS 2016年第34期55卷 9625-9637页

作者： Du, Yuxin Tong, Minming Zhou, Lingling Dong, Haibo China Univ Min & Technol Sch Informat & Elect Engn Xuzhou 221008 Peoples R China

The application of visual technology to mine robots has become a hot topic in the development of coal mine automatic production. Key techniques of robot control are the feature recognition of sampled videos and the perception of complex surroundings. However, it is difficult for features in underground images with dark hue and low target discrimination to be recognized and extracted, especially for reasons of the nonuniform illumination and heavy dust concentration in mines. Hence, an edge detection algorithm based on the Retinex theory and wavelet multiscale product is proposed in this paper for low-light-level mine image feature extraction, which employs a modified multiscale Retinex method to deal with the low frequency subplot after the wavelet decomposition, an improved fuzzy enhancement approach to handle high frequency components, and finally a revised multiscale product edge detection algorithm to obtain the ultima edge image. Compared with a variety of algorithms by detecting edges of both normal illuminated and underground images, experimental results show that with characteristics of high real-time performance and detection accuracy, the proposed algorithm can exactly meet the needs of surrounding environment perception for mine robots, which applies well to image edge detection in low illumination mines. (C) 2016 Optical Society of America

关键词： Digital image processing Edge detection Feature extraction Fourier transforms image processing Optical control systems

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image quality and dose differences caused by vendor-specific image processing of neonatal radiographs

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PEDIATRIC RADIOLOGY 2016年第11期46卷 1606-1613页

作者： Sensakovic, William F. O'Dell, M. Cody Letter, Haley Kohler, Nathan Rop, Baiywo Cook, Jane Logsdon, Gregory Varich, Laura Florida Hosp Imaging Adm 601 E Rollins St Orlando FL 32803 USA

image processing plays an important role in optimizing image quality and radiation dose in projection radiography. Unfortunately commercial algorithms are black boxes that are often left at or near vendor default settings rather than being optimized. We hypothesize that different commercial image-processing systems, when left at or near default settings, create significant differences in image quality. We further hypothesize that image-quality differences can be exploited to produce images of equivalent quality but lower radiation dose. We used a portable radiography system to acquire images on a neonatal chest phantom and recorded the entrance surface air kerma (ESAK). We applied two image-processing systems (Optima XR220amx, by GE Healthcare, Waukesha, WI;and MUSICA(2) by Agfa HealthCare, Mortsel, Belgium) to the images. Seven observers (attending pediatric radiologists and radiology residents) independently assessed image quality using two methods: rating and matching. image-quality ratings were independently assessed by each observer on a 10-point scale. Matching consisted of each observer matching GE-processed images and Agfa-processed images with equivalent image quality. A total of 210 rating tasks and 42 matching tasks were performed and effective dose was estimated. Median Agfa-processed image-quality ratings were higher than GE-processed ratings. Non-diagnostic ratings were seen over a wider range of doses for GE-processed images than for Agfa-processed images. During matching tasks, observers matched image quality between GE-processed images and Agfa-processed images acquired at a lower effective dose (11 +/- 9 mu Sv;P < 0.0001). image-processing methods significantly impact perceived image quality. These image-quality differences can be exploited to alter protocols and produce images of equivalent image quality but lower doses. Those purchasing projection radiography systems or third-party image-processing software should be aware that image processing c

关键词： Chest image processing image quality Neonate Radiation dose Radiography

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Comparison of envelope detection techniques in coherence scanning interferometry

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APPLIED OPTICS 2016年第24期55卷 6763-6774页

作者： Gianto, G. Salzenstein, F. Montgomery, P. Univ Strasbourg CNRS ICube Lab 23 Rue Loess F-67037 Strasbourg France

The aim of this work is to make a comparison of the most current signal processing techniques used to analyze the fringe signal in coherence scanning interferometry (CSI), a major technique for optical surface roughness measurements. We focus here on classical AM-FM signal-processing algorithms such as the Hilbert transform (HT), the five-sample adaptive (FSA), and the continuous wavelet transform (CWT). We have recently also introduced a new family of compact and robust algorithms using the Teager-Kaiser energy operator (TKEO). We propose an improved version of TKEO using a combination of different techniques of pre-filtering and demodulation processing to remove the noise and offset component and to retrieve the fringe envelope to either determine the surface height information or to separate adjacent transparent layers. In particular, as a pre-filtering approach, we have focused on empirical mode decomposition in combination with the Savitzky-Golay filter. An added Gaussian post-filtering is helpful for a precise peak extraction. The experimental results show that TKEO performs better than CWT in terms of computation time and provides a better surface extraction than HT and FSA. Results have been obtained on synthetic and real data taken from a layer of resin on a silicon substrate. (C) 2016 Optical Society of America.

关键词： image processing Fringe analysis Interferometric imaging Imaging systems

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Efficient System of Cracking-Detection algorithms with 1-mm 3D-Surface Models and Performance Measures

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JOURNAL OF COMPUTING IN CIVIL ENGINEERING 2016年第6期30卷 1-16页

作者： Zhang, Allen Wang, Kelvin C. P. Ji, Ran Li, Qiang Joshua Oklahoma State Univ Dept Civil & Environm Engn 207 Engn South Stillwater OK 74078 USA

The paper proposes an interactive algorithm for a three-dimensional (3D) surface that can substantially improve its cracking detection performance by adjustments based on the observer's feedback. Since the correct response to the observer's feedback is critical to the performance of an interactive algorithm, the paper presents a series of novel methodologies to accomplish the interaction between the detection system and the observer with a high level of success. A computer program is developed to establish the interactive detection system and implement two levels of detection. The bottom level is automated and can be used to find the majority of cracking. The top level is assisted by the users and can be applied for semi-automated refinement. In particular, the top level is designated to find missed cracks or delete noises within user-defined regions. The techniques of precision recall and confusion matrix are used to determine effectiveness of the developed system of algorithms. The results from the case study on a highly cracked pavement segment indicate that the automated level of the proposed interactive system can achieve high detection accuracy with appropriate training, and the assisted level can retrieve nearly all cracks missed by the automated level and delete almost all noises from the processing using the automated level.

关键词： DETECTORS CRACKING of pavements algorithms INTERACTIVE computer systems SEGMENTATION (image processing) GABOR filters TEXTURE analysis (image processing) NEURAL networks (Computer science)

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Appearance based background subtraction for PTZ cameras

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SIGNAL processing-image COMMUNICATION 2016年 47卷 417-425页

作者： Sajid, Hasan Cheung, Sen-ching S. Jacobs, Nathan Univ Kentucky Ctr Visualizat & Virtual Environm Lexington KY 40506 USA

Traditional background subtraction algorithms assume the camera is static and are based on simple per-pixel models of scene appearance. This leads to false detections when the camera moves. While this can sometimes be addressed by online image registration, this approach is prone to dramatic failures and long-term drift. We present a novel background subtraction algorithm designed for pan-tilt-zoom cameras that overcomes this challenge without the need for explicit image registration. The proposed algorithm automatically trains a discriminative background model, which is global in the sense that it is the same regardless of image location. Our approach first extracts multiple features from across the image and uses principal component analysis for dimensionality reduction. The extracted features are then grouped to form a Bag of Features. A global background model is then learned from the bagged features using Support Vector Machine. The proposed approach is fast and accurate. Having a single global model makes it computationally inexpensive in comparison to traditional pixel-wise models. It outperforms several state-of-the-art algorithms on the CDnet 2014 pan-tilt-zoom and baseline categories and Hopkins155 dataset. In particular, it achieves an F-Measure of 75.41% on the CDnet dataset PTZ category, significantly better than the previously reported best score of 62.07%. These results show that by removing the coupling between detection model and spatial location, we significantly increase the robustness to camera motion. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Background subtraction Foreground detection image segmentation

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Detection of Face Position and Orientation Using Depth Data

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8th International Conference on image processing and Communications (IP and C)

作者： Szwoch, Mariusz Pieniazek, Pawel Gdansk Univ Technol Gdansk Poland

ISBN: (纸本)9783319238142;9783319238135

In this paper an original approach is presented for real-time detection of user's face position and orientation based only on depth channel from a Microsoft Kinect sensor which can be used in facial analysis on scenes with poor lighting conditions where traditional algorithms based on optical channel may have failed. Thus the proposed approach can support, or even replace, algorithms based on optical channel or based on skeleton or face tracking information. The accuracy of proposed algorithms is 91% and was verified on Facial Expressions and Emotions Database using 169 recordings of 25 persons. As the processing time is below 20 ms per frame on a standard PC, the proposed algorithms can be used in real-life applications. The presented algorithms were validated in a prototype application for user emotion recognition based on depth channel information only.

关键词： Face detection Depth image processing Kinect sensor

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Sequence-to-Sequence Similarity-Based Filter for image Denoising

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IEEE SENSORS JOURNAL 2016年第11期16卷 4380-4388页

作者： Panetta, Karen Bao, Long Agaian, Sos Tufts Univ Dept Elect & Comp Engn Medford MA 02155 USA Univ Texas San Antonio Dept Elect Engn San Antonio TX 78249 USA

image denoising has been a well-studied problem for imaging systems, especially imaging sensors. Despite remarkable progress in the quality of denoising algorithms, persistent challenges remain for a wide class of general images. In this paper, we present a new concept of sequence-to-sequence similarity (SSS). This similarity measure is an efficient method to evaluate the content similarity for images, especially for edge information. The approach differs from the traditional image processing techniques, which rely on pixel and block similarity. Based on this new concept, we introduce a new SSS-based filter for image denoising. The new SSS-based filter utilizes the edge information in the corrupted image to address image denoising problems. We demonstrate the filter by incorporating it into a new SSS-based image denoising algorithm to remove Gaussian noise. Experiments are performed over synthetic and experimental data. The performance of our methodology is experimentally verified on a variety of images and Gaussian noise levels. The results demonstrate that the proposed method's performance exceeds several current state-of-the-art works, which are evaluated both visually and quantitatively. The presented framework opens up new perspectives in the use of SSS methodologies for image processing applications to replace the traditional pixel-to-pixel similarity or block-to-block similarity.

关键词： image denoising Gaussian noise evaluation similarity imaging sensor

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Band selection and evaluation with spatial information

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INTERNATIONAL JOURNAL OF REMOTE SENSING 2016年第19期37卷 4501-4520页

作者： Cao, Xianghai Han, Jungong Yang, Shuyuan Tao, Dacheng Jiao, Licheng Xidian Univ Minist Educ Key Lab Intelligent Percept & Image Understanding Xian 710071 Shaanxi Provinc Peoples R China Northumbria Univ Dept Comp Sci & Digital Technol Newcastle Upon Tyne Tyne & Wear England Univ Technol Sydney Ctr Quantum Computat & Intelligent Syst Sydney NSW Australia

Spatial information has been widely used for hyperspectral image classification, which can dramatically improve the classification accuracy. Though band selection is an important preprocessing step for hyperspectral image processing, spatial information has not been well exploited in this field. In this article, we will exploit the spatial information for band selection. This article mainly includes two parts: algorithm design, and algorithm evaluation. In the first part, we propose an efficient band selection method by using the spatial structure information and spectral information. In the second part, we advocate the use of the local spatial filtering and the spectral-spatial classifier for evaluating the performance of band selection algorithms instead of the traditional pixel-wise classifiers. Comprehensive experiments over diverse publicly available benchmark data sets reveal some interesting results.

关键词： HYPERSPECTRAL imaging systems algorithms -- Evaluation BEAMFORMING PIXEL density measurement BIG data

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HypeRvieW: an open source desktop application for hyperspectral remote-sensing data processing

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INTERNATIONAL JOURNAL OF REMOTE SENSING 2016年第23期37卷 5533-5550页

作者： Garea, Alberto S. Ordonez, Alvaro Heras, Dora B. Arguello, Francisco Univ Santiago de Compostela Ctr Singular Invest Tecnoloxias Informac CiTIUS Santiago De Compostela Spain Univ Santiago de Compostela Dept Elect & Computac Santiago De Compostela Spain

In this article, we present a desktop application for the analysis, reference data generation, registration, and supervised spatial-spectral classification of hyperspectral remote-sensing images through a simple and intuitive interface. Regarding the classification ability, the different classification schemes are implemented by using a chain structure as a base. It consists of five configurable stages that must be executed in a fixed order: preprocessing, spatial processing, pixel-wise classification, combination, and post-processing. The modular implementation makes its extension easy by adding new algorithms for each stage or new classification chains. The tool has been designed as a platform that is open to the incorporation of algorithms by the users interested in comparing classification schemes. As an example of use, a classification scheme based on the Quick Shift (QS) algorithm for segmentation and on Extreme Learning Machines (ELMs) or Support Vector Machines (SVMs) for classification is also proposed. The application is license-free, runs on the Linux operating system, and was developed in C language using the GTK library, as well as other free libraries to build the graphical user interfaces (GUIs).

关键词： HYPERSPECTRAL imaging systems REMOTE sensing image processing SUPPORT vector machines GRAPHICAL user interfaces (Computer systems) INFORMATION storage & retrieval systems

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Real-time digital image stabilization based on regional field image gray projection

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Journal of systems Engineering and Electronics 2016年第1期27卷 224-231页

作者： Weiping Yang Zhilong Zhang Yan Zhang Xinping Lu Jicheng Li Zhiguang Shi School of Electronic Science and Engineering National University of Defence Technology

Digital image stabilization technique plays important roles in video surveillance and object *** useful electronic image stabilization algorithms have been studied.A real-time algorithm is proposed based on field image gray projection which enables the regional odd and even field image to be projected into x and y directions and thus to get the regional gray projection curves in x and y directions,*** the odd field image channel,motion parameters can be estimated via iterative minimum absolute difference based on two successive field image regional gray projection *** motion compensations can be obtained after using the Kalman filter ***,the odd field image is adjusted according to the *** the mean time,motion compensation is applied to the even field image channel with the odd field image gray projection curves of the current *** minimizing absolute difference between odd and even field image gray projection curves of the current frame,the inter-field motion parameters can be ***,the even field image can be adjusted by combining the inter-field motion parameters and the odd field ***,the stabilized image sequence can be obtained by synthesizing the adjusted odd and even field *** results show that the proposed algorithm can run in real-time and have a good stabilization *** addition,image blurring can be improved.

关键词： image dithering field based processing electronic image stabilization regional gray projection minimum absolute difference.

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