基于彩色图像的人民币新旧识别算法仿真

人民币新旧程度的识别算法是改善纸币清分效果的关键.针对目前采用灰度直方图算法来区分纸币新旧程度,识别效果易受光照条件影响的问题,提出了基于HSI颜色格式的彩色图像纸币新旧识别算法:取色度H分量和饱和度S分量作为特征参数,分别计算色调H和饱和度S直方图.提取计算样本图像的色度直方图和饱和度直方图与模板图像的相关系数.由相关系数的量化结果,设计不同的阈值,根据相似程度的不同,判断结果将纸币分为"新"、"一般"和"旧"3个等级.并通过实验验证了该算法的可行性和优越性.     

Development of Habitat Suitability Criteria and In‐Stream Habitat Assessment for the Benthic Cyanobacteria Phormidium

Global demand for freshwater has led to unprecedented levels of water abstraction from riverine systems. This has resulted in large alterations in natural river flows. The deleterious impacts of reduced flows on fish and macroinvertebrate abundances have been thoroughly investigated; in contrast, there is a limited understanding of the potential for changes in the abundance of nuisance benthic algal/cyanobacterial blooms. In New Zealand, Phormidium sp. blooms are common in numerous rivers during summer low flows. In this study, an in‐stream habitat assessment is used to examine the relationship between Phormidium habitat availability and reducing flows. Over 650 observations of Phormidium mats, from seven sites (Hutt River, lower North Island, New Zealand), were used to construct habitat suitability curves for depth, velocity and substrate. Preference curves were fitted using both the ‘forage ratio’ and ‘quantile regression’ methods. Phormidium growth, observed at all seven sites, increased significantly from upstream (uppermost site, 5.2% mat cover) to downstream (63.5%). The habitat suitability curves revealed Phormidium had a large tolerance to velocity, depth and substrate type. Consequently, decreases in flow had only negligible effects on available Phormidium habitat. During periods of stable flow, Phormidium abundance positively correlated with increased nitrogen concentrations, potentially explaining the large variation in Phormidium cover from upstream to downstream. Quantile regression generated habitat suitability criteria were a more accurate predictor of available Phormidium habitat than the forage ratio criteria. Copyright © 2013 John Wiley & Sons, Ltd.     

HSI空间亮度信息的多尺度Retinex图像增强研究

彩色图像增强可以提高图像的亮度,增强图像的对比度和细节,同时使得图像颜色更加逼真自然,并且较少失真,在遥感、医学、刑侦、电视与多媒体等许多方面具有良好的应用前景和重要的理论研究意义。提出基于HSI空间亮度信息的多尺度Retinex图像增强算法（HSI_MSR）,算法通过对HSI颜色空间模型的分析,通过增强HSI模型中I分量,将HSI模型转换到RGB模型,得到增强后的彩色图像。通过仿真实验可知HSI_MSR算法可以较好地提高图像的视觉特性,亮度适合人眼观察,细节较为丰富,使得图像颜色更加逼真自然。     

一种基于遗传算法的彩色图像分割改进算法

图像分割是进行图像理解的基础,也是图像工程技术中一个重要的问题.近几年来关于图像的分割方法层出不穷,但随着多媒体技术和Internet技术的发展,彩色图像分割处理的准确性和实时性要求也越来越高.为此提出了一种基于遗传算法的彩色图像分割改进算法.经过大量的对比实验表明,用这种方法分割目标和背景区域差别较大的彩色图像具有分割效果好、实时性、鲁棒性强的特点,是一种较为理想的分割方法.     

多阶段车牌定位算法

车牌定位是车牌识别系统中的关键环节.针对车牌图像区域丰富的边缘信息以及独特的特征,提出一种实用而有效的车牌定位方法.首先,将原始图像转换到HSI空间上,利用图像的字符边缘特征信息和数学形态学操作对目标区域进行粗定位;然后,根据车牌固有的特征定义4种不同的特征值,通过自组织神经网络的训练,实现对车牌区域的精确定位.最后,对80幅彩色图像进行测试,其有效率可达96.25%.     

基于HSI彩色空间模型的域替换降噪算法

对彩色数字图像进行降噪处理时,为兼顾标量处理法的简便性和矢量处理法的有效性,提出一种对彩色空间域实行替换的方法。采用均值滤波法在RGB域内进行滤波处理,将图像数据从RGB域转换到HSI域,用滤波处理后的H域、S域替换含有噪声的H域、 S域。对由双目内窥镜采集的实际彩色图像进行实验,结果证明该域替换法可以结合标量处理和矢量处理的优点,达到比一般标量处理法及简单矢量处理法更好的降噪效果。     

基于HSI颜色空间的蔗糖结晶图像分割方法

针对煮糖过程蔗糖结晶图像的特点,采用颜色空间转换的方法,将图像从RGB颜色空间转换到HSI颜色空间,利用HSI颜色空间各分量相对独立性以及结晶颗粒和糖浆溶液的色调差异通过改进的大津法对H分量进行阈值分割,再通过数学形态学,中值滤波,孔洞填充,去除噪声颗粒,去除图像边界的非完整颗粒等方法进行后续处理,最终将结晶颗粒从复杂的图像信息中分割出来。实验证明该方法分割效果好,切实可行。     

Color image segmentation in HSI space for automotive applications

This article presents a method for classifying color points for automotive applications in the Hue Saturation Intensity (HSI) Space based on the distances between their projections onto the SI plane. Firstly the HSI Space is analyzed in detail. Secondly the projection of image points from a typical automotive scene onto the SI plane is shown. The minimal classes relevant for driver assistance applications are derived. The requirements for the classification of the points into those classes are obtained. Several weighting functions are proposed and a fast form of an euclidean metric is investigated in detail. In order to improve the sensitivity of the weighting function, dynamic coefficients are introduced. It is shown how to compute them automatically in order to get optimal results for the classification. Finally some results of applying the metric to the sample images are shown and the conclusions are drawn.

新型高光谱图像的超分辨率制图方法

由于高光谱图像的应用在很大程度上受限于其较低的空间分辨率,为此提出了一种结合支持向量机和小波变换的高光谱图像超分辨率制图方法．先对高光谱图像进行光谱解混得到分量图,然后对分量图进行一级小波分解．各局域窗内中心像元的3个高频系数与邻域像元低频系数之间的对应关系表示为训练样本,用于支持向量机的学习．训练好的模型用来对低分辨率图像即分量图进行超分辨率制图．实验表明,这种借助小波变换来获取训练样本的学习方法无需先验信息,相比采用BP神经网络学习的方法,支持向量机的超分辨率制图效果更佳．     

基于背景分割技术的水面运动目标提取

基于背景分割技术提出了一种复杂背景下水面运动目标提取算法。在算法的第1阶段，采用统计差分图像方法分割出无运动的岸上背景区域，同时获得场景中的运动区域，包括水面及水面运动目标。在算法的第2阶段，根据水面区域在HSI色彩空间中的统计信息，运用基于Mahalanobis距离的决策方法，分析得到运动区域中的水面部分.图像中最后留下的部分即是运动目标。实验表明，该算法能够稳定地实现对水面目标的提取及跟踪。