图像纹理区检测及分割算法研究

图像纹理区是指在进行边缘检测时边缘分布相对密集,并存在一些伪边缘的区域。研究表明,现有的很多图像处理算法的误差集中在纹理区。图像纹理区分割的目的就是将这一区域分割出来以便对其采用不同的处理方法。本文提出了一种基于模糊增强的图像纹理区检测及分割算法。本文算法根据图像纹理区特点,首先增强纹理区像素对比度,并利用Canny边缘检测算法提高纹理区检测效果,最终实现了图像纹理区的准确检测和分割。

城市纹理断裂商业街区规划弥合--以厦门市台湾商业街区改造规划为例

弥合城市纹理断裂商业街区纹理缺失,增强商业街区活力,是现代城市管理者及规划师面临的现实而具有挑战的问题。本文以厦门市台湾商业街区改造规划为例,通过新要素的介入,旧要素的更新利用,在历史传承和现状更新基础上,考虑街区功能、文化、环境、交通等四个方面新旧要素的交替作用,实现商业街区公共空间的回归,创造新城市空间和公共生活。

基于模糊增强的图像区域分割算法研究

针对图像平坦区、纹理区和清晰边缘的分割问题,提出了一种基于模糊增强的图像分割算法。该算法依据基于模糊增强的Canny边缘检测原理,在充分分析图像纹理区和清晰边缘的像素分布特点的基础上,通过增强纹理区像素对比度,检测出更多的纹理区细节。并利用膨胀、区域连通等方法实现了图像的区域分割。实验结果表明,该算法能够准确地实现了图像平坦区、纹理区和清晰边缘的分割,并有较强的抗噪能力。图像分割结果可以反映更多的纹理细节信息。

基于高阶和非局部全变分的核磁共振图像重构算法

为了更好地提高核磁共振图像(magnetic resonance image,MRI)重构质量,提出了一种基于高阶和非局部全变分的混合重构算法。首先,该算法采用全局梯度提取法分离待重构MRI图像的平滑区和边缘纹理区;在算法的每次迭代过程中,先对平滑区采用高阶全变分(higher degree total variation,HDTV)算法,然后对边缘纹理区采用非局部全变分(non-local total variation,NLTV)算法;最后,将算法迭代结束后的平滑区和边缘纹理区图像合并就是重构图像。实验发现,该算法的重构效果大大优于TV(total variation,全变分)、HDTV、NLTV算法,其重构图像既能有效地滤除噪声和保留纹理细节信息,又大大抑制了全变分的阶梯效应。

基于边缘检测的SVD水印

介绍了一种基于边缘检测的分块SVD水印嵌入方法,其计算简单、定位准确,且运算量小,有利于数字水印的不可见性和鲁棒性之间的平衡。

典型图像分类算法分析

本文主要讨论了图像处理中基于人类视觉系统(HVS)的图像区域分类的相关概念、技术以及算法的实现。图像分类是指将图像分成平滑区、纹理区和边缘区,它是图像处理中一种重要的手段,具有广泛的应用。所谓平滑区就是指图像中灰度变化较少,包含信息量少,能量小的部分;而边缘是图像中一种灰度突变形式的集合;纹理是表征象素按一定的排列规律进行重复排列的部分。纹理区和边缘区的图像块具有较大的能量。本文主要基于人类视觉的一些特性,提出了空域和频域两种分类算法,这两种算法都是先将图像分块,然后再与人类视觉特性相结合,对各个图像块进行处理,再确定相应划分区域的阈值,对原始图像进行二次分类,最终得到图像的平滑区、纹理区和边缘区.

Cultivation Influences on Soil Organic Carbon Associated with Texture in Seasonally Frozen Zones

[Objective] This study aimed to examine indicative roles of texture representing soil organic carbon presence and variability subsequent to cultivation under cold temperate climates with seasonal freeze-thaw events. [Method] Three chronosequences were selected for paired comparisons. Soil samples were collected at six depths with a 10 cm increment. Analysis of variance with general linear model and regression was performed for statistical analysis. [Result] In seasonally frozen soils where fragmentation of macroaggregates was stimulated, soil organic carbon level was positively associated with clay + silt proportion due to a wider textural range, better than sole clay content. Exponential function better fitted the experimental data to present progressively increased effectiveness of clay + silt content in maintaining carbon. Clay content explained 12%-41% and 14%-43% of variation via linear and exponential functions, respectively. Accordingly, clay + silt content explained 47%-65% and 46%-70%. [Conclusion] Texture reflected soil organic carbon occurrence as consequences of reclamation. For seasonally frozen soils with wider textural ranges, it is robust to adapt clay + silt content as dependent variable and exponential function. The generated algorithms provided an available pathway to estimate soil organic carbon losses following cultivation and to evaluate soil fertility.

Study on mechanism of circumferential cracks in cold-region tunnels

There exists frost damage in cold-region tunnels. The circumferential cracks affect the function of tunnels. Using three-dimensional finite element method, the authors analyzed the mechanism of circumferential cracks in cold-region tunnels It is proved that the internal thermal stress in lining exceeds the tensile strength of concrete, which is the direct cause for circumferential cracks occurring. The laws of thermal stress in lining induced by parameters such as temperature drop, horizontal drag coefficient and length of lining are analyzed. The conclusions are valuable to the design and construction of cold-region tunnels considering the thermal stress.

Segmentation of High Spatial Resolution Remote Sensing Images of Mountainous Areas Based on the Improved Mean Shift Algorithm

Using conventional Mean Shift Algorithm to segment high spatial resolution Remote sensing images of mountainous areas usually leads to an unsatisfactory result, due to its rich texture information. In this paper, we propose an improved Mean Shift Algorithm in consideration of the characteristics of these images. First, images were classified into several homogeneous color regions and texture regions by conducting variance detection on the color space. Next, each homogeneous color region was directly segmented to generate the preliminary results by applying the Mean Shift Algorithm. For each texture region, we conduct a high-dimensional feature space by extracting information such as color, texture and shape comprehensively, and work out a proper bandwidth according to the normalized distribution density. Then the bandwidth variable Mean Shift Algorithm was applied to obtain segmentation results by conducting the pattern classification in feature space. Last, the final results were obtained by merging these regions by means of the constructed cost functions and removing the oversegmented regions from the merged regions. It has been experimentally segmented on the high spatial resolution remote sensing images collected by Quickbird and Unmanned Aerial Vehicle(UAV). We put forward an approach to evaluate the segmentation results by using the segmentation matching index(SMI). This takes into consideration both the area and the spectrum. The experimental results suggest that the improved Mean Shift Algorithm outperforms the conventional one in terms of accuracy of segmentation.

Target Region Location Based on Texture Analysis and Active Contour Model

Traditional texture region location methods with Gabor features are often limited in the selection of Gabor filters and fail to deal with the target which contains both texture and non-texture parts.Thus,to solve this problem,a two-step new model was proposed.In the first step,the original features extracted by Gabor filters are applied to training a self-organizing map(SOM) neural network and a novel merging scheme is presented to achieve the clustering.A back propagation(BP) network is used as a classifier to locate the target region approximately.In the second step,Chan-Vese active contour model is applied to detecting the boundary of the target region accurately and morphological processing is used to create a connected domain whose convex hull can cover the target region.In the experiments,the proposed method is demonstrated accurate and robust in localizing target on texture database and practical barcode location system as well.

Research on Face Tracking in Community Monitoring System

This paper proposes a block Mean-Shift algorithm based on target real-time update and LBP texture features, through the target update improves the accuracy of target tracking, enhances the local character of the target through the target block, so as to improve the robustness of algorithm based on skin color backgrounds. And then analyze the Mean-Shift algorithm cannot recover quickly lost target tracking defects, and its improvement by combining the frame difference method.