Industrial Image Processing Using Fuzzy-logic
模糊逻辑在工业图像处理中的应用
Procedia Engineering, Volume 100, 2015, Pages 492-498
Abstract: This paper concerns with the utilization of artificial intelligence borrowed techniques such as fuzzy logic for the automatic analysis of X-ray images of industrial products for defect detection. An original two stages algorithm is presented based on the feature analysis of the radiographic images obtained from the inspected product. Each object in the image is analyzed using fuzzy logic techniques. The first stage takes an automatic decision whether the current object can be classified as a defect from the geometrical point of view and the second stage takes the final decision by using “logical” criteria that is dependent on the product at hand and its quality requirements.
Recent Advances in Optical Image Processing
光学图像处理技术最新进展
Progress in Optics, In Press, Corrected Proof, Available online 29 April 2015
Abstract: Optical processing of images has received much attention recently. Experimental breakthroughs have been achieved mainly by studying correlation applications for identification and tracking, two-dimensional and three-dimensional holography, compression and encryption of images, etc. While images are originally optical, numerical processing is often realized to fully exploit their information content. Within this context, our aim is to review the recent progress made in the field of optical processing of information. We consider techniques allowing us to increase image quality to render them more useful for correlation and reconstruction applications. The chapter is divided in two parts. In the first part, techniques for increasing image quality are described in detail. Interestingly, those dealing with color encoding are addressed. In addition, methods for denoising images are dealt with. The second part considers the polarization encoding methods. Throughout this review chapter, many examples illustrating the performances of these techniques are given. Future prospects for optimizing current techniques of optical processing of images are suggested.
TSGL a Thread Safe Graphics Library for Visualizing Parallelism
线程安全图形库在可视化“平行”中的应用
Procedia Computer Science, Volume 51, 2015, Pages 1986-1995
Abstract: Multicore processors are now the standard CPU architecture, and multithreaded parallel programs are needed to take full advantage of such CPUs. New tools are needed to help students learn how to design and build such parallel programs. In this paper, we present the thread-safe graphics library (TSGL), a new C + +11 library that allows different threads to draw to a shared Canvas, which is updated in approximate real-time. Using TSGL, instructors and students can create visualizations that illustrate multithreaded behavior. We present three multithreaded applications that illustrate the use of TSGL to help students see and understand how an application is using parallelism to speed up its computation.
Implementation and performance of a general purpose graphics processing unit in hyperspectral image analysis
超光谱图像分析通用图形处理器的运行与性能
International Journal of Applied Earth Observation and Geoinformation, Volume 26, February 2014, Pages 312-321
Abstract: A graphics processing unit (GPU) can perform massively parallel computations at relatively low cost. Software interfaces like NVIDIA CUDA allow for General Purpose computing on a GPU (GPGPU). Wrappers of the CUDA libraries for higher-level programming languages such as MATLAB and IDL allow its use in image processing. In this paper, we implement GPGPU in IDL with two distance measures frequently used in image classification, Euclidean distance and spectral angle, and apply these to hyperspectral imagery. First we vary the data volume of a synthetic dataset by changing the number of image pixels, spectral bands and classification endmembers to determine speed-up and to find the smallest data volume that would still benefit from using graphics hardware. Then we process real datasets that are too large to fit in the GPU memory, and study the effect of resulting extra data transfers on computing performance. We show that our GPU algorithms outperform the same algorithms for a central processor unit (CPU), that a significant speed-up can already be obtained on relatively small datasets, and that data transfers in large datasets do not significantly influence performance. Given that no specific knowledge on parallel computing is required for this implementation, remote sensing scientists should now be able to implement and use GPGPU for their data analysis.
Rough-fuzzy clustering and multiresolution image analysis for text-graphics segmentation
粗糙模糊聚类与多分辨率图像分析在文本图形分割中的应用
Applied Soft Computing, Volume 30, May 2015, Pages 705-721
Abstract: This paper presents a segmentation method, integrating judiciously the merits of rough-fuzzy computing and multiresolution image analysis technique, for documents having both text and graphics regions. It assumes that the text and non-text or graphics regions of a given document are considered to have different textural properties. The M-band wavelet packet analysis and rough-fuzzy-possibilistic c-means are used for text-graphics segmentation problem. The M-band wavelet packet is used to extract the scale-space features, which offers a huge range of possibilities of scale-space features for document image and is able to zoom it onto narrow band high frequency components. A scale-space feature vector is thus derived, taken at different scales for each pixel in an image. However, the decomposition scheme employing M-band wavelet packet leads to a large number of redundant features. In this regard, an unsupervised feature selection method is introduced to select a set of relevant and non-redundant features for text-graphics segmentation problem. Finally, the rough-fuzzy-possibilistic c-means algorithm is used to address the uncertainty problem of document segmentation. The whole approach is invariant under the font size, line orientation, and script of the text. The performance of the proposed technique, along with a comparison with related approaches, is demonstrated on a set of real life document images.
Segmentation of colon tissue sample images using multiple graphics accelerators
多功能图形加速器在结肠组织样本图像分割中的应用
Computers in Biology and Medicine, Volume 51, 1 August 2014, Pages 93-103
Abstract: Nowadays, processing medical images is increasingly done through using digital imagery and custom software solutions. The distributed algorithm presented in this paper is used to detect special tissue parts, the nuclei on haematoxylin and eosin stained colon tissue sample images. The main aim of this work is the development of a new data-parallel region growing algorithm that can be implemented even in an environment using multiple video accelerators. This new method has three levels of parallelism: (a) the parallel region growing itself, (b) starting more region growing in the device, and (c) using more than one accelerator. We use the split-and-merge technique based on our already existing data-parallel cell nuclei segmentation algorithm extended with a fast, backtracking-based, non-overlapping cell filter method. This extension does not cause significant degradation of the accuracy; the results are practically the same as those of the original sequential region growing method. However, as expected, using more devices usually means that less time is needed to process the tissue image; in the case of the configuration of one central processing unit and two graphics cards, the average speed-up is about 4–6×. The implemented algorithm has the additional advantage of efficiently processing very large images with high memory requirements.
3D graphics on the web: A survey
网络三维图形研究综述
Computers & Graphics, Volume 41, June 2014, Pages 43-61
Abstract: In recent years, 3D graphics has become an increasingly important part of the multimedia web experience. Following on from the advent of the X3D standard and the definition of a declarative approach to presenting 3D graphics on the web, the rise of WebGL has allowed lower level access to graphics hardware of ever increasing power. In parallel, remote rendering techniques permit streaming of high-quality 3D graphics onto a wide range of devices, and recent years have also seen much research on methods of content delivery for web-based 3D applications. All this development is reflected in the increasing number of application fields for the 3D web. In this paper, we reflect this activity by presenting the first survey of the state of the art in the field. We review every major approach to produce real-time 3D graphics rendering in the browser, briefly summarise the approaches for remote rendering of 3D graphics, before surveying complementary research on data compression methods, and notable application fields. We conclude by assessing the impact and popularity of the 3D web, reviewing the past and looking to the future.
On the second order spatiochromatic structure of natural images
自然图像二阶空-色结构研究
Vision Research, In Press, Uncorrected Proof, Available online 27 May 2015
Abstract: We provide a theoretical analysis of some empirical facts about the second order spatiochromatic structure of natural images in color. In particular, we show that two simple assumptions on the covariance matrices of color images yield eigenvectors made by the Kronecker product of Fourier features times the triad given by luminance plus color opponent channels. The first of these assumptions is second order stationarity while the second one is commutativity between color correlation matrices. The validity of these assumptions and the predicted shape of the PCA components of color images are experimentally observed on two large image databases. As a by-product of this experimental study, we also provide novel data to support an exponential decay law of the spatiochromatic covariance between pairs of pixels as a function of their spatial distance.
RGB Histogram Based Color Image Segmentation Using Firefly Algorithm
萤火虫算法在基于三原色直方图彩色图像分割中的应用
Procedia Computer Science, Volume 46, 2015, Pages 1449-1457
Abstract: In this paper, optimal multi-level image segmentation is proposed using the Firefly Algorithm (FA). In this work, RGB histogram of the image is considered for bi-level and multi-level segmentation. Optimal thresholds for each colour component are attained by maximizing Otsu's between-class variance function. The proposed segmentation procedure is demonstrated using standard RGB dataset and validated using the existing FA in the literature combined with three randomization search strategies, such as Brownian Distribution, Lévy Flight and the Gaussian distribution related random variable. The performance assessment between FAs is carried out using parameters, such as objective value, PSNR, SSIM and CPU time.
Semantic Image Analysis for Intelligent Image Retrieval
语义图像分析在智能图像检索中的应用
Procedia Computer Science, Volume 48, 2015, Pages 192-197
Abstract: Image understanding and analysis is the most exciting and fastest-growing research areas in the computer vision. Recent computer vision technologies and algorithms are support efficient semantic image analysis and retrieval. Image analysis is deal with image representation, estimation formula, and sampling density. Image analysis at semantic level is result in automatic extraction of image descriptions as per human perception which ultimately bridge semantic gap between low-level visual features and the high-level concepts capturing the conveyed meaning. Vital semantic image information is basically retrieved from image content, mainly from meaningful image objects and their mutual relations. In this paper, we present Semantic analysis of image by knowledge driven approach, start with Image content analysis with respect to semantic concepts, design image database and knowledge base on the basis of semantic content and retrieval, presentation and modification of image reference database or knowledge base for knowledge delivery intention. Experimental result shows improvement in image retrieval performance and accuracy.
