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1.
尺度空间形状描述属计算机视觉与模式识别领域内一个重研究课题,文章将介绍作者在这方面所做的工作。首先给出用形状特征曲线表示二维形状方法,然后用不同尺度的高斯拉普拉斯算子和高斯梯度算子求形状特征曲线过零点,最后用这些过零点,得到从粗到精确表示二维形状边界的多边形。实验结果表明,该方法既有效又简单。  相似文献   

2.
基于方向特征的二值商标图像检索方法   总被引:8,自引:1,他引:8  
文中针对二值商标图像,提出一种基于方向特征的商标图像检索方法。用边界方向直方图表示目标的边界方向特征,图像的相似性度量采用直方图求交算法;用区域方向直方图表示目标的区域方向特征。图像的相似性程度用直方图的相关距离来度量。这两者结合起来得到的方向特征可以同时反映图像的整体形状和轮廓形状。实验表明,方向特征能够有效地描述图像的形状及空间分布信息,取得了令人满意的检索结果。  相似文献   

3.
二维形状分类识别是计算机视觉和模式识别等领域的一个重要问题,在目标识别、图像理解等应用中发挥着重要作用。针对二维形状分类识别研究,主要从特征描述、形状分类识别、形状标准数据库三个方面综述了该方向近年来最新的研究工作。综合分析了二维形状特征表示方法,主要包括基于轮廓的、基于区域的、基于骨架的以及基于多特征融合的方法,并简要评述;介绍并分析了二维形状分类识别方法,主要包括传统机器学习分类器、集成分类器、深度学习方法等;概述了二维形状识别中常用的标准数据库;展望了二维形状识别分类研究的发展趋势。  相似文献   

4.
二维直方图区域斜分的最大熵阈值分割算法   总被引:6,自引:0,他引:6  
指出现有二维直方图区域直分法中存在明显的错分,提出一种二维直方图区域斜分方法.导出基于二维直方图区域斜分的最大熵阈值选取公式及其快速递推算法,给出图像分割结果和运行时间.并与基于二维直方图直分的最大熵原始算法及其快速算法进行比较.结果表明二维直方图区域斜分可使分割后的图像内部区域均匀,边界形状准确,更有稳健的抗噪性.本文算法的运行时间约为二维直方图斜分最大熵法原始算法的2%,不到二维直方图直分最大熵法的两种快速递推算法的1/3.  相似文献   

5.
密度分布特征及其在二值图像检索中的应用   总被引:1,自引:0,他引:1       下载免费PDF全文
图像的形状是描述图像的重要视觉和语义特征,可通过图像中像素点的区域分布表现出来。为了对二值图像进行有效检索,提出了一种基于区域的形状特征——密度分布特征,用来进行二值图像检索。该方法在经过形心定位和子图像区域划分后,可得到2个M维特征向量,其中第1个表示各个子图像区域的目标像素的相对密度,第2个表示各个子图像区域的目标像素在极坐标方向上的相对密度的一阶数值差分。在进行相似性度量时,首先采用Gaussian模型对用这2个特征向量计算得到的距离分别进行归一化处理;然后综合两个特征向量的距离计算总的相似度。实验结果表明,密度分布特征不仅能够有效地刻画二值图像的形状,具有非常好的平移、尺度和旋转不变性,而且检索结果优于Hu不变矩。  相似文献   

6.
首先基于边界上当前像素与前后两个相邻像素的坐标关系 ,定义并构造出边界像素与连通闭区域内 ,某些像素之间的联系 ,然后通过枚举各边界像素类型及其特点分析 ,提出了一种用于判定 ,并找出区域内与当前边界像素具有这种联系的像素系列 ,进而遍历出任意连通闭区域 (像素边界线可为任意复杂曲线的单连通或者复连通闭区域 )的像素遍历算法 .该算法在适应性及时间与空间性能等许多方面均很好地满足了诸如任意连通闭区域的填充和点在各种复杂区域的判定与跟踪等方面的应用需要 ,同时 ,它对闭区域像素的描述方法也为开展如何更有效地表示闭区域的研究提供了一种有益的参考 .  相似文献   

7.
用于数字图像直方图处理的一种二值映射规则   总被引:1,自引:1,他引:1       下载免费PDF全文
直方图表示数字图像中每一灰度级与其出现频数间的统计关系,它可给出图像的概貌性描述,而基于直方图修改技术的灰度变换是图像增强的实用而有效的处理方法之一。直方图处理包含均衡化和规定化两种技术。均衡化的目的是使图像像素均匀地分布在所有灰度级上;规定化的目的是将原图像的直方图转变为规定的直方图,以便突出一定灰度范围内的图像。为了进一步提高直方图处理算法的有效性,首先分析了现有的几种数字图像直方图均衡化和规定化算法存在的缺点,然后提出了一种新的二值映射规则(BML),该规则基于最优控制原理,以直方图误差最小为准则进行灰度映射,实验证明.该规则算法简单,无论是用于直方图均衡化处理.还是用于直方图规定化处理,均较其他映射规则都更为有效。  相似文献   

8.
王逸飞  陈雁秋 《计算机科学》2006,33(11):228-232
本文提出一种新的二维形状描述方法,用于描述二值和灰度图像物体的形状信息。该方法使用同心环状区域对二维形状进行分解,产生一组描述强度值的投影函数,并通过傅立叶变换实现旋转不变性和抗干扰能力。该方法与物体是否具有单一边界无关,能够适应各种复杂的、边界不规则的或者不连通的物体形状。此外,该方法还能够直接应用于灰度图象。  相似文献   

9.
基于二维Arimoto熵的阈值分割方法   总被引:1,自引:0,他引:1  
提出基于二维Arimoto熵的阈值分割方法.首先由图像的像素值及其邻域像素均值得到图像的二维直方图,然后从二维直方图中计算出二维Arimoto熵.当二维Arimoto熵达到最大时,对应的灰度级对即为分割阈值.通过引入二维联合幂概率分布建立快速算法,使算法速度大大提高,易于硬件实现.大量的对比实验表明,本文算法表现稳定,总体的分割效果优于基于二维Renyi熵和二维Shannon熵的阈值分割算法.  相似文献   

10.
距离分布直方图及其在商标图案检索中的应用   总被引:6,自引:1,他引:5       下载免费PDF全文
形状是描述图象的重要视觉特征,它可以通过像素点分布在空间不同的区域而表现出来,针对二值图象提出了一种基于区域的形状特征,即距离分布直方图,它的基本思想就是通过统计图象中像素点的距离区域的分布情况来获得形状特征。其中,基准点的选择和距离区域的划分是两具重要的部分,实验结果表明,距离分布直方图能够有效地刻画出二值图象的形状特征,并且具有非常好的平移。尺度和旋转不变性,将其应用于商标图案检索,其检索结果符合人眼的视觉感受。  相似文献   

11.
用不变矩和边界方向进行形状检索   总被引:10,自引:1,他引:10  
基于形状的图像检索一直以来是图像内容检索的一个难点问题,而目前采用周长、面积、边角率等描述形状的方法不能使形状检索达到理想的效果.本文提出了一种新的针对图像形状的检索方法.首先,用Canny算子对图像进行平滑处理,提取图像边界方向直方图特征、其次,用不变矩来描述图像形状的区域特征,不变矩特征不受图像的缩放、平移和旋转的影响.最后,为了克服不变矩只关心对象区域,而对图像边界忽视的缺点,提出了不变矩与边界方向特征相结合的方法,使得检索取得更好的效果.本文通过对医学图像的形状检索实验,给出了实验结果和结论.  相似文献   

12.
Machine vision systems are being increasingly used for sophisticated applications such as classification and process control. Though there is significant potential for the increased deployment of industrial vision systems, a number of important problems have to be addressed to sustain growth in the area of industrial machine vision. Artificial neural networks (ANNs) coupled with machine vision systems offer a new methodology for solving difficult computational problems in many areas of science and engineering. As a consequence, the research work presented in this paper investigates several novel uses of machine vision and ANNs in the processing of single camera multi-positional images for 2D and 3D object recognition and classification. Many industrial applications of machine vision allow objects to be identified and classified by their boundary contour or silhouette. Boundary contour information was chosen as an effective method of representing the industrial component, a composite signature being generated using vectors obtained from the generation of multi-centroidal positions and the boundary pixels.The composite signature can be re-sampled to form a suitable input vector for an ANN. Three different ANN topologies have been implemented: the multi-layer perceptron (MLP), a learning vector quantisation network (LVQ) and hybrid self-organising map (SOM). This method of representing industrial components has been used to compare the ANN architectures when implemented as classifiers based on shape and dimensional tolerance. A number of shortcomings with this methodology have been highlighted, most importantly the identification of a unique sequence start point, vital for rotation invariance. Another problem may arise due to the conflict between the inherent robustness of ANNs when dealing with noise, and classifying components which are similar but display subtle dimensional differences.  相似文献   

13.
一种基于边缘模式的直方图构造新方法   总被引:6,自引:0,他引:6  
基于图像边缘和噪音模式的分析,使用了一种目标和背景之间的边界检测方法;并基于边界的描述,提出了一种新的在边界两侧和边界内部选取相等数目的像素构造直方图的方法。该种直方图避免现有方法中全部像素直方图、加权直方图和内部像素直方图不适合于小目标的缺点,避免了边缘像素直方图抗噪能力差和阈值因图像边缘类型型变的缺点。该直方图能同时用于大目标和小目标时以及边界是阶跃边缘和屋顶状边缘时的阈值选取,具有很大的通用性和实用性。实验结果证明,使用该方法的直方图优于现有的直方图构造方法。  相似文献   

14.
15.
针对现有盲道识别率低,处理方式单一,且容易受光照、阴影的影响等问题,提出一种改进的盲道识别算法。该方法针对盲道颜色、纹理特性,分别利用颜色直方图特征的阈值分割结合改进的区域生长分割,灰度共生矩阵特征的模糊C均值聚类分割,结合Canny边缘检测和Hough变换算法,使得盲道区域与周围人行区域分开,确定出盲道的偏移方向。实验结果表明,该算法能够更加精准地分割多种类型盲道,检测出盲道区域的边界与行进方向,而且解决了部分光照和阴影问题,能够自适应选择速度最快而且高效的分割方法,可以应用在电子导盲等多种设备中。  相似文献   

16.
Omi T  Shinomoto S 《Neural computation》2011,23(12):3125-3144
The time histogram is a fundamental tool for representing the inhomogeneous density of event occurrences such as neuronal firings. The shape of a histogram critically depends on the size of the bins that partition the time axis. In most neurophysiological studies, however, researchers have arbitrarily selected the bin size when analyzing fluctuations in neuronal activity. A rigorous method for selecting the appropriate bin size was recently derived so that the mean integrated squared error between the time histogram and the unknown underlying rate is minimized (Shimazaki & Shinomoto, 2007 ). This derivation assumes that spikes are independently drawn from a given rate. However, in practice, biological neurons express non-Poissonian features in their firing patterns, such that the spike occurrence depends on the preceding spikes, which inevitably deteriorate the optimization. In this letter, we revise the method for selecting the bin size by considering the possible non-Poissonian features. Improvement in the goodness of fit of the time histogram is assessed and confirmed by numerically simulated non-Poissonian spike trains derived from the given fluctuating rate. For some experimental data, the revised algorithm transforms the shape of the time histogram from the Poissonian optimization method.  相似文献   

17.
Recognition of planar shapes is an important problem in computer vision and pattern recognition. The same planar object contour imaged from different cameras or from different viewpoints looks different and their recognition is non-trivial. Traditional shape recognition deals with views of the shapes that differ only by simple rotations, translations, and scaling. However, shapes suffer more serious deformation between two general views and hence recognition approaches designed to handle translations, rotations, and/or scaling would prove to be insufficient. Many algebraic relations between matching primitives in multiple views have been identified recently. In this paper, we explore how shape properties and multiview relations can be combined to recognize planar shapes across multiple views. We propose novel recognition constraints that a planar shape boundary must satisfy in multiple views. The constraints are on the rank of a Fourier-domain measurement matrix computed from the points on the shape boundary. Our method can additionally compute the correspondence between the curve points after a match is established. We demonstrate the applications of these constraints experimentally on a number of synthetic and real images.  相似文献   

18.
Segmentation of color lip images by spatial fuzzy clustering   总被引:2,自引:0,他引:2  
In this paper, we describe the application of a novel spatial fuzzy clustering algorithm to the lip segmentation problem. The proposed spatial fuzzy clustering algorithm is able to take into account both the distributions of data in feature space and the spatial interactions between neighboring pixels during clustering. By appropriate pre- and postprocessing utilizing the color and shape properties of the lip region, successful segmentation of most lip images is possible. Comparative study with some existing lip segmentation algorithms such as the hue filtering algorithm and the fuzzy entropy histogram thresholding algorithm has demonstrated the superior performance of our method.  相似文献   

19.
Efficient near-duplicate image detection is important for several applications that feature extraction and matching need to be taken online. Most image representations targeting at conventional image retrieval problems are either computationally expensive to extract and match, or limited in robustness. Aiming at this problem, in this paper, we propose an effective and efficient local-based representation method to encode an image as a binary vector, which is called Local-based Binary Representation (LBR). Local regions are extracted densely from the image, and each region is converted to a simple and effective feature describing its texture. A statistical histogram can be calculated over all the local features, and then it is encoded to a binary vector as the holistic image representation. The proposed binary representation jointly utilizes the local region texture and global visual distribution of the image, based on which a similarity measure can be applied to detect near-duplicate image effectively. The binary encoding scheme can not only greatly speed up the online computation, but also reduce memory cost in real applications. In experiments the precision and recall, as well as computational time of the proposed method are compared with other state-of-the-art image representations and LBR shows clear advantages on online near-duplicate image detection and video keyframe detection tasks.  相似文献   

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