Texture crack detection

Automatic visual inspection has become one of the active research issues in machine vision technology in the past decades. Most of the methodologies developed address the problems of defect detection on a nontextured or regularly textured surface. However, problems in detecting defects on a randomly textured surface, especially cracks, have not received much attention. In this paper, we present a novel algorithm that uses a Wigner model to identify cracks in complex textural backgrounds, regardless of whether the inspected surface is randomly or regularly textured. We also investigate the windowing characteristics of the Wigner distribution and their impact on crack detection. Some of the Brodatz' natural texture images have been used for evaluating the performance of the algorithm. Promising results are obtained and presented in this paper.     

闪光X光噪声图象的局部统计滤波

本文介绍一种噪声图象的滤波方法 ,它不需要先验的图象模型 ,而且也不会损伤边界和细小的细节 ,在相加性和相乘性噪声的情况下 ,计算与边界方向有关的子集的局部平均值和方差 ,相应地沿着边界方向的噪声就被去掉 ,同时对边界有一定的增强效果     

Target differentiation with simple infrared sensors using statistical pattern recognition techniques

This study compares the performances of various statistical pattern recognition techniques for the differentiation of commonly encountered features in indoor environments, possibly with different surface properties, using simple infrared (IR) sensors. The intensity measurements obtained from such sensors are highly dependent on the location, geometry, and surface properties of the reflecting feature in a way that cannot be represented by a simple analytical relationship, therefore complicating the differentiation process. We construct feature vectors based on the parameters of angular IR intensity scans from different targets to determine their geometry and/or surface type. Mixture of normals classifier with three components correctly differentiates three types of geometries with different surface properties, resulting in the best performance (100%) in geometry differentiation. Parametric differentiation correctly identifies six different surface types of the same planar geometry, resulting in the best surface differentiation rate (100%). However, this rate is not maintained with the inclusion of more surfaces. The results indicate that the geometrical properties of the targets are more distinctive than their surface properties, and surface recognition is the limiting factor in differentiation. The results demonstrate that simple IR sensors, when coupled with appropriate processing and recognition techniques, can be used to extract substantially more information than such devices are commonly employed for.     

The S-kernel: A measure of symmetry of objects

In this paper we introduce a new symmetry feature named “symmetry kernel” (SK) to support a measure of symmetry. Given any symmetry transform S, SK of a pattern P is the maximal included symmetric sub-set of P for all directions and shifts. We provide a first algorithm to exhibit this kernel where the centre of symmetry is assumed to be the centre of mass. Then we prove that, in any direction, the optimal axis corresponds to the maximal correlation of a pattern with its symmetric version. That leads to a second algorithm. The associated symmetry measure is a modified difference between the respective surfaces of a pattern and its kernel. A series of experiments supports the actual algorithm validation.     

Comparison among feature extraction methods for HIV-1 protease cleavage site prediction

Recently, several works have approached the HIV-1 protease specificity problem by applying a number of methods from the field of machine learning. However, it is still difficult for researchers to choose the best method due to the lack of an effective comparison. For the first time we have made an extensive study on methods for feature extraction for the problem of HIV-1 protease. We show that a fusion of classifiers trained in different feature spaces permits to obtain a drastically error reduction with respect to the performance of the state-of-the-art.     

AKIMA方法在EXAFS谱解析中的应用

解析扩展Ｘ射线吸收精细结构谱（ＴｈｅＥｘｔｅｎｄｅｄＸ－ｒａｙＡｂｓｏｒｐｔｉｏｎＦｉｎｅＳｔｒｕｃｔｕｒｅＥＸＡＦＳ）的一种方法是曲线拟合，在曲线拟合中，能量阈值Ｅ０的确定有着很重要的意义，同时也有相当的难度，本文应用ＡＫＩＭＡ平滑数据点方法达到了对Ｅ０在数学意义上的精确求解，数据分析结果表明，这种方处理结果是令人满意的。     

InP与In_（1－x）Ga_xAs_yP_（1－y）／InP的电解液电调制反射

研究了ＩｎＰ样品和Ｉｎ１－ｘＧａｘＡｓｙＰ１－ｙ液相外延片在３００～８００ｎｍ范围内的电调制反射光谱。利用Ａｐｓｎｅｓ三点法计算了临界点能量、增宽因子和自旋轨道分裂值。通过实验曲线与理论公式的拟合，确定了临界点能维数及相位因子。并且间接提供了被测Ｉｎ１－ｘＧａｘＡｓｙＰ１－ｙ四元合金的组份值及其它临界点能量值Ｅ０和Ｅ２。     

中国低空大气波导出现概率和波导特征量的统计分析

本文简要说明了我们对大气波导的统计方法，并对统计结果作了讨论和分析。文中详细讨论了中国低空大气波导在不同地区的出现情况，说明了它们在各地出现概率随季节月份的变化情况及日变化情况，还说明了悬空波导和贴地波导基本分布状况；对于波导顶高、强度、厚度、高度等特征量，主要给出了它们的平均值和波导在不同数值上的分布。结果表明，我国低空大气波导出现的高概率区是南部沿海、东南沿海、东部沿海和西北地区中部；我国的四大高原、天山以北和东北平原是无波导区；我国低空大气波导的顶高一般在地面上２０００ｍ以内，强度在０～２０Ｍ单位之间，厚度一般是１００～５００ｍ，高度是西北地区绝大部分为０米，沿海地区大多数超过３００ｍ。同时文中也讨论了我国低空大气波导的分布和我国各地的具体地理位置、气候条件的相关情况。     

半导体激光器高速驱动源

本文介绍满足ＤＦＢ激光器高速特性测试要求的一种半导体激光器高速驱动源的设计要点、测试结果和使用情况。     

基于灰度共生矩阵的图像纹理特征提取分析

图像纹理作为一种重要的视觉手段,是图像中普遍存在而又难以描述的特征。目前常用的纹理特征提取的方法主要有统计方法、模型方法、信号处理方法和结构方法。灰度共生矩阵即为灰度级的空间相关矩阵,以其为基础的统计方法通过对矩阵统计量的求取较好地提取到了纹理特征,通过选取关键参数编程并进行仿真实现,分别求取了四个方向的灰度共生矩阵及其特征量来分析图像的纹理特征。