基于3D直方图的彩色图象分割方法

以阈值分割技术为基础，提出了基于3D直方图的生长法和尺度空间聚类方法。分别利用3D空间中同一类目标像素频度的连通性的尺度空间聚类原理，简单而有效地解决了多维阈值分割带来的过度分割问题。该方法对不同类型图象具有很好的适应性，并已成功应用于医学彩色图象处理领域。     

Simulated image of electrospun nonwoven web of PVA and corresponding nanofiber diameter distribution

Fiber diameter is the most important characteristic in electrospun nonwoven webs. Understanding how it is influenced by the electrospinning parameters is essential to produce webs with desired characteristics. In this contribution, Direct Tracking method for measuring electrospun fiber diameter is described. To evaluate the accuracy of the technique, a simulation algorithm for generating webs with known characteristics was employed. To verify the applicability of the method on real samples, an electrospun polyvinyl alcohol (PVA) mat, as a representative of real webs, was used. Since the Direct Tracking method uses a binary image as its input, local thresholding was applied to segment the SEM micrograph of the electrospun web. The results indicate that the method could be used successfully for determining fiber diameter in electrospun nonwoven webs.     

基于关联能量系数的图像分割新算法

针对现有熵阈值法在理论上存在的不足和计算复杂性过大的缺陷,提出了一种基于随机变茸概率分布之间的关联能量系数的阈值法,方法通过最小化日标和背景两个概率分布之间的关联能耸系数推导出了一种选取最佳分割阈值的新算法.实验结果表明,提出的关联能量系数阈值分割方法是可行的,有效的.方法可以弥补现有方法的不足,具有一定的普遍适应性,可以推广到日标和背景符合任意概率分布的图像进行最佳阈值选取.     

Development of high-accuracy image centroiding algorithm for CMOS-based digital sun sensors

A digital sun sensor calculates the incident sunlight angle using the sunlight image registered on a Complimentary Metal Oxide Semiconductor (CMOS) image sensor. In order to accomplish this, an exact center of the sunlight image has to be determined. Therefore, an accurate estimate of the centroid is the most important factor in digital sun sensor development. The most general method for determining the centroid is the thresholding method, and this method is also the simplest and easy to implement. Another centering algorithm often used is the image filtering method that utilizes image processing. The sun sensor accuracy using these methods, however, is quite susceptible to noise in the detected sunlight intensity. This is especially true in the thresholding method where the accuracy changes according to the threshold level. In this paper, a template method that uses the sunlight image model to determine the centroid of the sunlight image is suggested, and the performance has been compared and analyzed. The template method suggested, unlike the thresholding and image filtering method, has comparatively higher accuracy. In addition, it has the advantage of having consistent level of accuracy regardless of the noise level, which results in a higher reliability.     

Error based criterion for on-line wavelet data compression

Wavelet based data compression methods have demonstrated superior performance over the conventional interpolative methods. However, the wavelet based methods need thresholding on the wavelet domain coefficients. Since wavelet coefficients are not commonly intuitive to engineers, significant a priori knowledge of either the wavelet coefficients or process thresholds is required. So unless thresholds are pre-specified, this requirement makes wavelets unsuitable for on-line implementations. Furthermore, as the relation between the wavelet domain coefficients and the measures of the quality of compression [root mean square error (RMSE) and local point error (LPE)] is not straightforward, it is difficult to achieve good control over the quality of compression by specifying thresholds on the wavelet coefficients. In this paper, an error based criterion is proposed for online wavelet data compression. It uses semantically straightforward measures of the quality of the result to be obtained to adaptively calculate the thresholds. Given a bound on time domain error limits like the RMSE and LPE, this technique adaptively computes the threshold values in wavelet domain. Experiments show that the resulting algorithm gives superior compression as compared to other wavelet based methods. Most importantly, it can be used on-line and provides an effective way of controlling LPE and RMSE. Finally, this method can easily be extended to other on-line wavelet applications such as data rectification and de-noising.     

Detection of partial occlusions of assembled components to simplify the disassembly tasks

An automatic disassembly cell requires of a computer vision system for recognition and localization of the products and each of theirs components. The detection of occlusions adds more information to the knowledge base to identify components and products, and generate a trustworthy and precise relational model (generic graph of hierarchic relations among the different components that make up the product). In this paper, a method to detect partial occlusions in assembled components is presented. This method is based on the fusion of regions and edges information, and it offers a certain degree of simplification for the recognition and modelled of the disassembly tasks, of the set of components which compose the product. The proposed approach to detect regions is a hybrid approach between RGB and HSV spaces. The bi-dimensional histogram V/S is employed for the selection of the appropriate thresholds which serve as an aid to diminish the influence of the highlights and shadows in images. The goal of this paper is to present an approach for the detection of occlusions in assembled components from a combination of HSV and RGB spaces, a bi-dimensional histogram and an edge detector.     

Color image segmentation based on homogram thresholding and region merging

In this paper, a color image segmentation approach based on homogram thresholding and region merging is presented. The homogram considers both the occurrence of the gray levels and the neighboring homogeneity value among pixels. Therefore, it employs both the local and global information. Fuzzy entropy is utilized as a tool to perform homogram analysis for finding all major homogeneous regions at the first stage. Then region merging process is carried out based on color similarity among these regions to avoid oversegmentation. The proposed homogram-based approach (HOB) is compared with the histogram-based approach (HIB). The experimental results demonstrate that the HOB can find homogeneous regions more effectively than HIB does, and can solve the problem of discriminating shading in color images to some extent.     

基于小波变换消除信号噪声的研究

利用小波方法去噪是小波分析工程实际的一个重要方面。简单介绍了小波分解和重构,小波去噪原理,硬阈值法、软阈值法、平移不变量法。并且利用Matlab将几种典型的信号叠加高斯白噪声进行仿真。     

基于二维直方图的模糊门限化方法

针对一维模糊度不能反映图像空间信息的缺点,本文提出了图像二维模糊度的概念,并将其用于门限化,二维门限矢量将二维直方图分为四个象限,其中对角线上的两种象限分别对应着目标象素类和背景象素类,而反对角线上的两种象限则对应着边缘象素和噪声象素,此方法为目标象限和背景象限中的每个元素赋予-[1/2,1]内的隶属度,以反映其属于目标或背景的程度,通过极大化这两个象限的某一模糊测度之和进行门限选择,实验表明,二维模糊方法的效果明显优于一维方法。     

光纤图像的定位二值化

本文介绍一种用于光纤图像分割的定位二值化方法.本方法根据光纤图像中光纤的位置和大小都固定的特点,首先通过两个方向的倾斜投影确定光纤中心的位置,接着由最小误差法确定是否存在光纤的初判阈值,然后根据光纤的大小选择合适的二值化区域,再在所定区域内进行二值化,从而将图像中所有光纤完整地、正确地分割出来.本方法避免了整体阈值法动态范围小和传统自适应阈值法固定分区所造成的误判.