汉字签名自动辨识的一种结构描述方法

在充分分析了签名图像的基础上提出了一种针对汉字签名利用结构描述来进行签名自动辨识的方法。其基本思想是在汉字骨架基础上提取构成汉字的各个基本笔段并同时提取表征各笔段的特征值，从而形成带有属性的模式串，以便进行串的比较并根据一定的判断准则给出判断结果。     

A simple method for automatically locating the nipple on mammograms

This paper outlines a simple, fast, and accurate method for automatically locating the nipple on digitized mammograms that have been segmented to reveal the skin-air interface. If the average gradient of the intensity is computed in the direction normal to the interface and directed inside the breast, it is found that there is a sudden and distinct change in this parameter close to the nipple. A nipple in profile is located between two successive maxima of this parameter; otherwise, it is near the global maximum. Specifically, the nipple is located midway between a successive maximum and minimum of the derivative of the average intensity gradient; these being local turning points for a nipple in profile and global otherwise. The method has been tested on 24 images, including both oblique and cranio-caudal views, from two digital mammogram databases. For 23 of the images (96%), the rms error was less than 1 mm at image resolutions of 400 μm and 420 μm per pixel. Because of its simplicity, and because it is based both on the observed behavior of mammographic tissue intensities and on geometry, this method has the potential to become a generic method for locating the nipple on mammograms     

A method for automatically finding multiple operating points in nonlinear circuits

A new algorithm based on a SPICE-like simulator that searches for multiple operating points automatically, with no user intervention required, is presented. This algorithm, which exploits the asymmetrical properties of nonlinear mappings that describe multistable circuits, has been implemented into a program which automatically finds multiple (in most cases, all) operating points of a circuit. In addition to finding multiple operating points, this method offers another feature: it is capable of detecting the stability of a particular operating point. Another useful feature of this method is that it allows the user to gauge how close a particular circuit is to possessing multiple operating points. For circuits known to possess multiple operating points, this method allows the user to specify which operating point is encountered first. Unlike other continuation methods, circuit element models are not modified; only augmenting resistors are required. Hence, this approach lends itself well as an "add-on" to existing circuit simulators. A number of circuit examples are given.     

应用于DM648的FLASH自动加载实现方法

为实现DSP嵌入式系统的应用程序自动加载功能,提出了基于TI公司的TMS320DM648的NOR Flash自动加载实现方法.首先对启动过程进行了分析,给出了用户加载程序的编写方法.在此基础上,根据公共目标文件格式和应用镜像脚本两种文件格式的说明,设计出公共目标文件格式到应用镜像脚本转换程序,生成可用于FLASH烧写的文件.最后在TMS320DM648核心板上实现了在CCS环境下对Flash编程和程序自动加载,证明该方法有效可行.     

Optimum mesh grading for finite-difference method

The coarseness error of the finite-difference (FD) method is studied analyzing a typical planar waveguide and a rectangular coaxial geometry. Results for equidistant and graded mesh are compared in terms of accuracy and numerical efforts. Because of the field singularities involved a graded mesh proves to be superior compared to the equidistant case. A grading strategy with optimum efficiency is presented. Furthermore, the results show that the most significant improvement in accuracy can be obtained by incorporating the edge behavior into the FD scheme     

自动识别信号PRF调制的新方法

对信号脉冲重复频率(PRF)的调制样式进行自动识别是信息处理领域的关键技术之一.为解决PRF调制识别算法识别样式有限、准确率低等问题,以雷达信号为例,提出了一种新的识别算法.对接收到的信号序列分别提取比值特征、比重特征、频率特征和形状特征4个参数.基于径向基概率神经网络,实现对多种信号PRF调制样式的自动识别.仿真结果表明:在脉冲丢失率和脉冲虚警率均为10%的情况下,利用该方法可以得到最低为90%的识别准确率,能够满足当前的电磁环境,具有一定的工程参考价值.     

A novel method for the automatic grading of retinal vessel tortuosity

Tortuosity is among the first alterations in the retinal vessel network to appear in many retinopathies, such as those due to hypertension. An automatic evaluation of retinal vessel tortuosity would help the early detection of such retinopathies. Quite a few techniques for tortuosity measurement and classification have been proposed, but they do not always match the clinical concept of tortuosity. This justifies the need for a new definition, able to express in mathematical terms the tortuosity as perceived by ophthalmologists. We propose here a new algorithm for the evaluation of tortuosity in vessels recognized in digital fundus images. It is based on partitioning each vessel in segments of constant-sign curvature and then combining together each evaluation of such segments and their number. The algorithm has been compared with other available tortuosity measures on a set of 30 arteries and one of 30 veins from 60 different images. These vessels had been preliminarily ordered by a retina specialist by increasing perceived tortuosity. The proposed algorithm proved to be the best one in matching the clinically perceived vessel tortuosity.     

Multi-scale directional-filtering-based method for follicular lymphoma grading

Follicular lymphoma (FL) is a group of malignancies of lymphocyte origin that arise from lymph nodes, spleen, and bone marrow in the lymphatic system. It is the second most common non-Hodgkins lymphoma. Characteristic of FL is the presence of follicle center B cells consisting of centrocytes and centroblasts. Typically, FL images are graded by an expert manually counting the centroblasts in an image. This is time consuming. In this paper, we present a novel multi-scale directional filtering scheme and utilize it to classify FL images into different grades. Instead of counting the centroblasts individually, we classify the texture formed by centroblasts. We apply our multi-scale directional filtering scheme in two scales and along eight orientations, and use the mean and the standard deviation of each filter output as feature parameters. For classification, we use support vector machines with the radial basis function kernel. We map the features into two dimensions using linear discriminant analysis prior to classification. Experimental results are presented.     

基于深度学习的钢材金相图像晶粒度等级评定方法

准确地评定钢材金相组织晶粒度等级能检测材料劣化情况,保障设备的服役安全。针对传统人工评定钢材金相组织晶粒度等级的方法耗时久且易受人工经验影响,评价结果一致性差且不可重复等问题,提出了一种基于深度学习的钢材金相晶粒度等级评定方法。在U-net模型上添加跳跃连接层并减少下采样次数来提高模型的分割准确率并减少网络参数量,在117张验证集上的像素准确率达93.86%,平均像素准确率(mean pixel accuracy,MPA)达86.89%,网络参数量仅为2.02 M。对晶界预测结果进行数字图像处理并结合截点法进行晶粒度等级评定,在测试图像上评定钢材晶粒度等级平均耗时仅8.3 s/张。与人工评级方法相比,本文方法具有准确性、高效性及可重复性。     

一种基于图像处理的高精度自动线宽测量方法

文章提出一种高精度的自动线宽测量方法,在PCB板图像中,通过矩形框选定被测量的线路部分,对该矩形框内的图像进行处理,精确定位线路边缘,获取线宽测量结果,经验证在不同倍率情况下测量值稳定在一个像素以内。     

一种用于雷达信号调制分类的特征评估方法

针对用于调制分类过程中雷达信号脉内特征参数评估问题,提出了一种多指标联合评估方法.该方法使用复杂性、可分离性和稳定性3个指标对特征参数的调制分类性能进行联合评估,克服了传统评估手段仅使用单一指标难以进行全面科学评估的缺陷,并可以根据应用需求获取相应的最合理的综合评分值.理论分析和计算机仿真结果表明,该方法可以有效评估特征的调制分类性能,具有较强的工程应用价值.     

Erratum to: Multi-scale directional-filtering-based method for follicular lymphoma grading

A new decision-based algorithm has been proposed for the restoration of digital images which are highly contaminated by the saturated impulse noise (i.e., salt-and-pepper noise). The proposed denoising algorithm performs filtering operation only to the corrupted pixels in the image, keeping uncorrupted pixels intact. The present study has used a coupled window scheme for the removal of high density noise. It has used sliding window of increasing dimension, centered at any pixel and replaced the noisy pixels consecutively by the median value of the window. However, if the entire pixels in the window are noisy, then the dimension of sliding window is increased in order to obtain the noise-free pixels for median calculation. Consequently, this algorithm has been found to be able to remove the high density salt-and-pepper noise and also preserved the fine details of the four images, Lena, Elaine, Rhythm, and Sunny, used as test images in this study (The latter two real-life images have been acquired using Sony: Steady Shot DSC- S3000). Experimentally, it has been found that the proposed algorithm yields better peak signal-to-noise ratio, image enhancement factor, structural similarity index measure and image quality index, compared with the other state-of-art median-based filters viz. standard median filter, adaptive median filter, progressive switched median filter, modified decision-based algorithm and modified decision-based unsymmetric trimmed median filter.     

A hybrid color and frequency features method for face recognition

This correspondence presents a novel hybrid Color and Frequency Features (CFF) method for face recognition. The CFF method, which applies an Enhanced Fisher Model (EFM), extracts the complementary frequency features in a new hybrid color space for improving face recognition performance. The new color space, the RIQ color space, which combines the R component image of the RGB color space and the chromatic components I and Q of the YIQ color space, displays prominent capability for improving face recognition performance due to the complementary characteristics of its component images. The EFM then extracts the complementary features from the real part, the imaginary part, and the magnitude of the R image in the frequency domain. The complementary features are then fused by means of concatenation at the feature level to derive similarity scores for classification. The complementary feature extraction and feature level fusion procedure applies to the I and Q component images as well. Experiments on the Face Recognition Grand Challenge (FRGC) version 2 Experiment 4 show that i) the hybrid color space improves face recognition performance significantly, and ii) the complementary color and frequency features further improve face recognition performance.     

An automatically paired two-dimensional direction-of-arrival estimation method for two parallel uniform linear arrays

In two-dimensional (2-D) direction-of-arrival (DOA) estimation, paring the azimuth and elevation angles of multiple sources is an important issue. In this letter, we propose a new automatically paired 2-D DOA estimation method by designing the geometry of two antenna subarrays and using the propagator method (PM). A special geometry between two parallel uniform linear arrays (ULAs) with a position displacement on the axial direction is proposed to facilitate the elevation and azimuth pairing and estimation. The simulation results have shown that the proposed method can achieve the same 2-D DOA estimation performance as the existing methods, while the complexity is reduced considerably.     

Strong consistency of the contraction mapping method for frequencyestimation

Some statistical properties in regard to the contraction mapping (CM) method are discussed. One of the requirements in this method is that the filter be parameterized to satisfy a certain fundamental property. The parameterization clearly depends on the normalized noise spectrum which theoretically has to be known or estimated a priori. If this information is available, one can first whiten the noise with a linear filter and then apply the CM method to the filtered data. In this way, the parameterization only needs to be done under the white noise assumption and filters like the AR(2) can be used by the CM method. In applications, however, prewhitening may not always be necessary     

A method for evaluating features of outlined components of an image

A method is proposed for accessing the inside of outlined contours so as to evaluate density features of the contoured regions while measuring their perimeter and area. Such features are among the most commonly used in biomedical image processing, but for large images their correct evaluation is not trivial unless to have an adequate amount of main memory available. This is especially true when the components of an image are outlined by methods which do not give rise to simple contours. Compared with other methods, the one we propose requires a much smaller amount of main memory, yet remaining fast enough for many purposes.     

Statistical coding method for facial features

Model-based techniques have been shown to give high compression rates for coding head and shoulder image sequences, typically for videophone applications. However, they lead to poor image quality in significant areas of the face such as the eyes and mouth. To overcome this problem, a hybrid system could be perceived where the facial features were represented using traditional statistical techniques and the remaining of the head and shoulder sequences using highly efficient model-based methods, therefore utilising more bits to code the sensitive areas and fewer for the rest. In the paper, the method of principal component analysis to code the dynamic changes in a sequence is presented     

A Bayes method for assessing product-reliability during developmenttesting

A fully Bayes approach is presented for analyzing product reliability during the development phase. Based on a Bayes version of the Barlow-Scheuer reliability-growth model, it is assumed that the product goes through a series of test/modification stages, where each product test yields attribute (pass-fail) data, and failure types are classified as fixable or nonfixable. Relevant information on both the failure probabilities and the reliability-growth process is used to motivate the prior joint distribution for the probability of each failure type over the specified range of testing. Results at a particular test-stage can be used to update the knowledge about the probability of each failure type (and thus product reliability) at the current test-stage as well as at subsequent test-stages, and at the end of the development phase. A relative ease of incorporation of prior information and a tractability of the posterior analysis are accomplished by using a Dirichlet distribution as the prior distribution for a transformation of the failure probabilities     

一种基于时频原子特征的雷达辐射源信号识别方法

提出了一种全新的基于时频原子特征的雷达辐射源信号识别方法.训练阶段,在过完备时频原子库的基础上,以类区分度为度量,提取少数最能区分不同类别信号的时频原子作为一组固定的特征;识别阶段,以原子和信号的内积的绝对值作为分类器的输入特征,采用有监督模糊自适应共振网络进行辐射源的自动识别.对5类典型雷达辐射源信号的实验结果表明,...