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1.
基于几何特征的在线手绘流程图识别   总被引:2,自引:0,他引:2  
为减少绘图设计软件繁琐的操作步骤,提出基于图元几何特征的在线手绘流程图识别方法.该方法首先识别用户笔画线元,对识别出的线元进行拟合并记录其属性信息,然后以流程图基本图形为单位,利用构成图元的笔画几何特征及笔画间的几何关系识别具体图形.整个识别过程简单、快捷、准确性较高,对用户绘图笔画顺序无要求,适用于不同用户的绘图习惯.  相似文献   

2.
针对目前大部分人脸表情识别算法中仅提取图像的某一类特征,导致特征参数不能全面反映脸部情感信息的问题,提出了一种基于特征融合和离散隐马尔可夫模型(HMM)识别的人脸表情识别方法。对同一个图像序列分别使用离散小波变换(DWT)和标准正交非负矩阵分解(ONMF)提取纹理信息,使用改进的主动表观模型(AAM)提取几何形变信息,再使用高维小样本下典型相关分析(CCA)对提取的两种特征进行特征融合,最后使用离散HMM来进行表情分类识别。实验结果表明,经过特征融合后,在较少特征向量维数下该方法能够达到较高的识别率和较快的识别速度。  相似文献   

3.
目的 为了克服手写输入中随意性强和自由度大的缺陷,同时兼顾简笔画的整体属性和局部特征,提出一种基于图元识别与感知哈希技术相结合的手写输入简笔画二级识别算法。方法 首先提取笔画的几何特征、笔序特征及结构特征且进行识别,然后查找由图元信息、笔画结构信息和笔序信息构成的简笔画语义库,完成由规则的几何图元构成的简笔画识别;若未被识别,则生成简笔画图像,利用感知哈希技术完成简笔画图像的识别。结果 基于本文提出的简笔画识别方法,实现了对样本库中150种简笔画对象的识别,平均识别率为82.6%。结论 实验结果表明,对于不同用户手写输入的任意样本库中的简笔画,该方法具有较高的识别率,此外,还可以通过在简笔画语义库和样本库中增加简笔画的种类等方式实现对更多种类简笔画的扩展识别。  相似文献   

4.
介绍了一种识别多笔画几何草图简单方法.它利用图形的暂时邻接关系和全局几何特征来识别一些简单的几何图形其中有实线和虚线类型,选择和删除手势.随着图形的旋转和尺度的变化这些几何特征(凸包、规则多边形的最小面积、周长和面积的数量比)是不变的.尽管多笔画的方法在选择合适的超时时间上存在问题,但这种方法可以得到令人满意的识别率.虽然在简单性和健壮性上更侧重于前者,但该方法已被证实适合交互式应用.  相似文献   

5.
手绘图形是人类思维外化和表达意图的一种有效方式,如何有效地提取手绘在图纸上的图形元素是理解绘图者意图的关键问题。鉴于手绘图形是由基本图元组合构成,采用层次结构逐步实现图元提取的思想,提出了一种手绘基本图元(线段、弧、圆和椭圆)的离线识别方法。在提取图形笔画骨架像素的基础上,跟踪骨架像素得到图形的直线段描述;通过对直线段序列的分析,进行直线段序列的断开和连接处理,形成图元的曲线段描述,通过对图元曲线段描述的分析得出图元的几何参数。实验表明,该方法能够以高精确度快速识别出图像中包含的手绘图元,具有良好的稳定性  相似文献   

6.
实现计算机图纸理解的关键在于对图纸中符号的识别,该文提出了一种建筑平面CAD图纸中符号识别的新方法,该方法首先由建筑符号中的几何图元构造出一种矩形网格结构,并用图元与网格之间的约束替换几何图元之间的约束来建立符号的几何特征描述。基于这种描述提出了一个统一的识别方法,最后给出了应用实例,取得了满意的识别效果。  相似文献   

7.
对通过手写板、光笔、数字笔等输入设备绘制的几何图形,采用基于图元表示法进行识别.该方法首先把输入的笔画组分解为图元(直线、园、圆弧等),对分割出来的各个图元进行识别,进而对识别的图元进行排序及位置关系提取,最后对图形进行拟合规整、输出识别结果.识别过程简单,速度快,准确率高,与输入笔序无关.  相似文献   

8.
提出了一种笔画分区矩特征的提取方法。根据汉字笔画分布特点,利用小波变换将汉字分解为4个方向笔画分量,用分区矩分别描述4个笔画于图像,并采用K—L变换对特征进行降维处理。采用该特征对有限集手写体汉字进行识别,初步实验结果表明该方法十分有效。  相似文献   

9.
介绍了一种识别多笔画几何草图简单方法。它利用图形的暂时邻接关系和全局几何特征来识别一些简单的几何图形其中有实线和虚线类型,选择和删除手势。随着图形的旋转和尺度的变化这些几何特征(凸包、规则多边形的最小面积、周长和面积的数量比)是不变的。尽管多笔画的方法在选择合适的超时时间上存在问题,但这种方法可以得到令人满意的识别率。虽然在简单性和健壮性上更侧重于前者,但该方法已被证实适合交互式应用。  相似文献   

10.
针对传统隐马尔可夫模型(HMM)在识别对象时没有有效利用所识别对象的结构信息,提出了一种基于原图像分块的HMM。这种模型利用原图像的各个分块作为状态,因此具有相应的拓扑结构,可以为所识别对象的结构信息建模。为了增强模型的描述能力与精确性,采用二阶HMM,引入了终止状态,将其应用在手写数字识别中。考虑到手写数字的结构特点与模型的拓扑结构,提出了一种提取手写数字笔画特征的方法,即根据叉点提取各个笔段的特征向量。对MNIST字库进行测试,平均识别率为95.7%。  相似文献   

11.
Optical character recognition for cursive handwriting   总被引:5,自引:0,他引:5  
A new analytic scheme, which uses a sequence of image segmentation and recognition algorithms, is proposed for the off-line cursive handwriting recognition problem. First, some global parameters, such as slant angle, baselines, stroke width and height, are estimated. Second, a segmentation method finds character segmentation paths by combining gray-scale and binary information. Third, a hidden Markov model (HMM) is employed for shape recognition to label and rank the character candidates. For this purpose, a string of codes is extracted from each segment to represent the character candidates. The estimation of feature space parameters is embedded in the HMM training stage together with the estimation of the HMM model parameters. Finally, information from a lexicon and from the HMM ranks is combined in a graph optimization problem for word-level recognition. This method corrects most of the errors produced by the segmentation and HMM ranking stages by maximizing an information measure in an efficient graph search algorithm. The experiments indicate higher recognition rates compared to the available methods reported in the literature  相似文献   

12.
由于受到面部五官、饰物等因素的影响,传统几何活动轮廓模型获取人脸外轮廓会产生凹陷、分片等现象.针对人脸图像的特点,将边缘外张力能量及肤色能量与全局能量结合,提出一种基于混合能量泛函的几何活动轮廓模型,有效地避免了这些问题.首先,根据演化曲线的邻域信息赋予边缘点向外的张力,使曲线能够克服面部特征及面部饰物的干扰,引导其向外轮廓方向演化.鉴于肤色是面部最重要的特征,提出肤色能量,进一步提高了模型的鲁棒性.此外,提出一种基于单高斯模型的改进算法,能够估计出接近实际人脸外轮廓的初始位置,为轮廓演化奠定了基础.在两个公共人脸库上进行测试,该方法能够得到准确的人脸分割效果;以手工分割的结果为基准,该算法定位精度明显优于传统的全局能量模型和局部能量模型.还用日常照片创建一个包含不同姿态、光照、复杂背景等因素、复杂的人脸库,分割结果表明,该方法能够克服这些因素的影响,取得了准确而稳定的人脸分割结果.  相似文献   

13.
Wongyu  Seong-Whan  Jin H. 《Pattern recognition》1995,28(12):1941-1953
In this paper, a new method for modeling and recognizing cursive words with hidden Markov models (HMM) is presented. In the proposed method, a sequence of thin fixed-width vertical frames are extracted from the image, capturing the local features of the handwriting. By quantizing the feature vectors of each frame, the input word image is represented as a Markov chain of discrete symbols. A handwritten word is regarded as a sequence of characters and optional ligatures. Hence, the ligatures are also explicitly modeled. With this view, an interconnection network of character and ligature HMMs is constructed to model words of indefinite length. This model can ideally describe any form of handwritten words, including discretely spaced words, pure cursive words and unconstrained words of mixed styles. Experiments have been conducted with a standard database to evaluate the performance of the overall scheme. The performance of various search strategies based on the forward and backward score has been compared. Experiments on the use of a preclassifier based on global features show that this approach may be useful for even large-vocabulary recognition tasks.  相似文献   

14.
提出一种基于点特征匹配和几何型哈希法的图像检索方法。利用小波变换提取图像的突变点,以点为辜心划定一小块区域,将图像划分成图像块。提取块的低层次特征矢量,将两幅图像之间的匹配转换成图像块之间的匹配。并采用几何型哈希索引方法实现图像的快速检索。实验证明,这种方法能够取得较高的检索精度,且对图像形变以及局部遮挡等都有较好的适应能力。  相似文献   

15.
Switching Linear Dynamic System (SLDS) models are a popular technique for modeling complex nonlinear dynamic systems. An SLDS can describe complex temporal patterns more concisely and accurately than an HMM by using continuous hidden states. However, the use of SLDS models in practical applications is challenging for three reasons. First, exact inference in SLDS models is computationally intractable. Second, the geometric duration model induced in standard SLDSs limits their representational power. Third, standard SLDSs do not provide a principled way to interpret systematic variations governed by higher order parameters. The contributions in this paper address all of these three challenges. First, we present a data-driven MCMC (DD-MCMC) sampling method for approximate inference in SLDSs. We show DD-MCMC provides an efficient method for estimation and learning in SLDS models. Second, we present segmental SLDSs (S-SLDS), where the geometric distributions of the switching state durations are replaced with arbitrary duration models. Third, we extend the standard SLDS model with additional global parameters that can capture systematic temporal and spatial variations. The resulting parametric SLDS model (P-SLDS) uses EM to robustly interpret parametrized motions by incorporating additional global parameters that underly systematic variations of the overall motion. The overall development of the extensions for SLDSs provide a principled framework to interpret complex motions. The framework is applied to the honey bee dance interpretation task in the context of the on-going BioTracking project at the Georgia Institute of Technology. The experimental results suggest that the enhanced models provide an effective framework for a wide range of motion analysis applications.  相似文献   

16.
In this paper a system for laboratory rodent video tracking and behavior segmentation is proposed. A new real-time mouse pose estimation method is proposed based on semi-automatically generated animal shape model. Behavior segmentation into separate behavior acts is considered as a signal segmentation problem using hidden Markov models (HMM). Conventional first order HMM supposes a geometric prior distribution on segment’s length, which is inadequate for behavior segmentation. We propose a modification of conventional first order HMM that allows any prior distribution on segment’s length. Experiments show that the developed approach can lead to more adequate results comparing to conventional HMM.  相似文献   

17.
视频技术的广泛应用带来海量的视频数据,仅依靠人力对监控视频中的异常进行检测是不太可能的。异常行为的自动化检测在公共安全等领域的地位极其重要。提出一种综合考虑目标特性和时空上下文的异常检测方法,该方法利用光流纹理图描述移动物体的刚性特征,建立基于隐马尔可夫模型HMM的时间上下文异常检测模型。在此基础上,提取异常目标的Radon特征,以支持向量机SVM的异常预分类结果为基础,通过HMM建立异常场景的空间上下文分类模型。该模型在公共数据集UCSD PED2上进行了实验验证,结果表明,本算法不仅在异常检测方面优于已有算法,而且还能给出异常分类。  相似文献   

18.
In this paper, we present a method for action categorization with a modified hidden conditional random field (HCRF). Specifically, effective silhouette-based action features are extracted using motion moments and spectrum of chain code. We formulate a modified HCRF (mHCRF) to have a guaranteed global optimum in the modelling of the temporal action dependencies after the HMM pathing stage. Experimental results on action categorization using this model are compared favorably against several existing model-based methods including GMM, SVM, Logistic Regression, HMM, CRF and HCRF.  相似文献   

19.
Parametric hidden Markov models for gesture recognition   总被引:7,自引:0,他引:7  
A method for the representation, recognition, and interpretation of parameterized gesture is presented. By parameterized gesture we mean gestures that exhibit a systematic spatial variation; one example is a point gesture where the relevant parameter is the two-dimensional direction. Our approach is to extend the standard hidden Markov model method of gesture recognition by including a global parametric variation in the output probabilities of the HMM states. Using a linear model of dependence, we formulate an expectation-maximization (EM) method for training the parametric HMM. During testing, a similar EM algorithm simultaneously maximizes the output likelihood of the PHMM for the given sequence and estimates the quantifying parameters. Using visually derived and directly measured three-dimensional hand position measurements as input, we present results that demonstrate the recognition superiority of the PHMM over standard HMM techniques, as well as greater robustness in parameter estimation with respect to noise in the input features. Finally, we extend the PHMM to handle arbitrary smooth (nonlinear) dependencies. The nonlinear formulation requires the use of a generalized expectation-maximization (GEM) algorithm for both training and the simultaneous recognition of the gesture and estimation of the value of the parameter. We present results on a pointing gesture, where the nonlinear approach permits the natural spherical coordinate parameterization of pointing direction  相似文献   

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