On-Line Recognition of Handwritten Chinese Characters

For the design of a system for on-line recognition of handwritten Chinesecharacters stroke segment ordering is such a difficult problem no good solution is availableto it yet so far.An optimal stroke segment matching algorithm based on stroke structureinformation is proposed in this paper.Results of experiments are presented so thatcomparison can be made between the proposed algorithm and the stroke segmentmatching method based on the strokes’absoulute coordinates.

An Efficient Text Recognition System from Complex Color Image for Helping the Visually Impaired Persons

The challenge faced by the visually impaired persons in their day-today lives is to interpret text from documents.In this context,to help these people,the objective of this work is to develop an efficient text recognition system that allows the isolation,the extraction,and the recognition of text in the case of documents having a textured background,a degraded aspect of colors,and of poor quality,and to synthesize it into speech.This system basically consists of three algorithms:a text localization and detection algorithm based on mathematical morphology method(MMM);a text extraction algorithm based on the gamma correction method(GCM);and an optical character recognition(OCR)algorithm for text recognition.A detailed complexity study of the different blocks of this text recognition system has been realized.Following this study,an acceleration of the GCM algorithm(AGCM)is proposed.The AGCM algorithm has reduced the complexity in the text recognition system by 70%and kept the same quality of text recognition as that of the original method.To assist visually impaired persons,a graphical interface of the entire text recognition chain has been developed,allowing the capture of images from a camera,rapid and intuitive visualization of the recognized text from this image,and text-to-speech synthesis.Our text recognition system provides an improvement of 6.8%for the recognition rate and 7.6%for the F-measure relative to GCM and AGCM algorithms.

Application of Matlab in Meteorological Graphic Recognition

Based on the characteristics of an original meteorological chart, Matlab software is used to design an algorithm that can independently extract some meteorological information from literature and analyze the data. Through the digitization of meteorological charts, it is easy to analyze and process meteorological chart data.

Graphic Processing Unit-Accelerated Neural Network Model for Biological Species Recognition

A graphic processing unit (GPU)-accelerated biological species recognition method using partially connected neural evolutionary network model is introduced in this paper. The partial connected neural evolutionary network adopted in the paper can overcome the disadvantage of traditional neural network with small inputs. The whole image is considered as the input of the neural network, so the maximal features can be kept for recognition. To speed up the recognition process of the neural network, a fast implementation of the partially connected neural network was conducted on NVIDIA Tesla C1060 using the NVIDIA compute unified device architecture (CUDA) framework. Image sets of eight biological species were obtained to test the GPU implementation and counterpart serial CPU implementation, and experiment results showed GPU implementation works effectively on both recognition rate and speed, and gained 343 speedup over its counterpart CPU implementation. Comparing to feature-based recognition method on the same recognition task, the method also achieved an acceptable correct rate of 84.6% when testing on eight biological species.

A Structure Similarity Analysis Method for On－Line Recognition of Handwritten Chinese Characters

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Data Pre－processing and Stroke Segment Extraction for On－line Handwritten Chinese Character Recognition

The stroke segments:' are proposed to be used as the basic features for handwritten Chinese character recognition. In this way, it is possible to overcome the difFiculties of unstable stroke information caused by stroke Joinings. The techniques of data pre-processing and stroke segment extraction have been described. In extracting stroke segment, not only the characteristics of the stroke itself, but also its absolute positions as well as relative positions with other strokes in the character have been taken into account.The primitive features for recognition were extracted under these comprehensive considerations.

The Architecture and Recognition Engine of a Chinese Pen-based Personal Data Assistant

The architecture and recognition engine of a newly-developed pen-based Chinese personal data assistant (PDA) are described in this paper. The PDA’s design principles of hardware and software architectures, basic features, and on-line Chinese handwritten character recognition system, are discussed in particular. Based on the architecture and recognition engine proposed in this paper, the first generation of pen-based Chinese PDA has been worked out and put into mass production.

基于图像内凹度的矿井外因火灾识别及抗干扰方法

尽早发现矿井火灾并处置,可避免或减少人员伤亡和财产损失及次生事故的发生。井下没有日光、月光、星光及闪电等自然光源,影响矿井火灾图像识别的主要是矿井光源。圆形度能够排除圆形光源的干扰,但难以排除非圆形光源的干扰。矩形度能够排除矩形光源的干扰,但难以排除非矩形光源的干扰。在工程实际中,因摄像机的拍摄角度不同,矿井光源图像会出现变形,无法呈现理想的规则形状,使用圆形度和矩形度算法难以排除矿井光源的干扰。揭示了火焰图像轮廓外接图面积明显大于其图像实际面积,圆形灯、长方形灯和正方形灯等矿井实际光源图像轮廓外接图面积近似等于其光源图像实际面积等特点。提出基于图像内凹度的矿井火灾识别及抗干扰方法,计算目标图像面积与图像轮廓外接图面积的比值(即图像内凹度),根据火焰图像内凹度数值较小,而矿井光源图像内凹度数值较大,区分火焰与矿井光源。提出的内凹度方法不受摄像机距检测目标距离和图像大小、摄像机安装位置和摄像机拍摄检测目标的角度、矿井光源形状等影响,适应性强,识别准确率高。实验表明,内凹度识别方法计算得到的矿井干扰光源减去火焰图像平均差值最大,波动最小,区分度最好,受摄像机拍摄角度及距离影响最小,抗干扰能力最强,准确率为91.6%。矩形度识别方法计算得到的矿井干扰光源减去火焰图像平均差值较大,波动较小,区分度较好,受摄像机拍摄角度及距离影响较小,抗干扰能力一般,准确率为72.5%。圆形度识别方法计算得到的矿井干扰光源减去火焰图像平均差值最小,波动最大,区分度最差,受摄像机拍摄距离影响较小,受摄像机拍摄角度影响大,抗干扰能力最差,准确率为12.0%。因此,提出的内凹度识别方法,优于矩形度和圆形度,区分度最好,受摄像机拍摄角度及距离影响最小,抗干扰能力最强。

基于九屏幕法的计算机绘图相似辨识方法研究

为了制止学生使用AutoCAD绘图在各类教学中的诸多图形相似行为,在TRIZ的九屏幕法启发下,提出基于AutoCAD绘图过程的相似辨识方法。利用ObjectARX开发了学生端记录辨识图形相似的特征信息插件,基于Python、Django、MySQL等开发了B/S模式的教师端图形相似辨识系统。先通过九屏幕法对问题进行分析,得到解决问题的资源;其次,分析学生绘图过程的产生相似图形的绘图方式;再次,分析这些绘图方式所引起的特征信息变化;然后,利用开发的插件将特征信息存入数据库;最后,使用这些特征信息来进行相似图档的辨识。通过教学实践表明这套方法可以有效制止学生图形相似,显著提高计算机绘图的教学效果。

身份认同视域下,街舞人群服装图形设计

近年来街舞运动热度颇高,酷飒的舞蹈动作、出众的潮流穿搭,率真直爽的生活态度,引起了年轻群体追求自我、表达个性的情感共鸣,进而对街舞文化展开了追寻,并逐步形成了特定的街舞人群,对标街舞人群的街头潮流服装市场也呈现出巨大的消费潜力。文章从身份认同的角度出发,明确身份认同、街舞人群的概念含义,明晰身份认同的产生条件要素。其次通过对街舞人群身份认同表征及街舞人群潮流服装图形设计的分析解读,探索针对街舞人群的潮牌服装图形设计方式。以期满足街舞人群借此获得身份认同感与归属感。

风景园林图像与图形在深度学习中的应用分析及未来展望

深度学习处理图像与图形数据的广泛应用,为风景园林研究的大样本数据获取、分析、预测,以及景观设计图的快速生成提供了新的解决思路与有效途径.本文以风景园林图像与图形为研究对象,剖析风景园林图像与图形的类型,探究其在深度学习技术中的应用途径,分别从图像识别、图像生成、图形预测三个方面出发,对国内外的相关文献进行分析总结,梳理应用进展,提出未来发展趋势可聚焦深度学习向迁移学习的转变、人工智能与创意思维的融合、物质属性与非物质属性的结合,并强调深度学习技术通过处理风景园林图像与图形在分析场所空间环境、自动生成景观表现图、快速智能化建模、科学预判人群行为偏好等方面发挥着巨大的作用,将其应用于风景园林领域,能够有效推动本学科的智慧化发展.

模型水轮机空化现象智能识别方法

为了更加准确地判断模型水轮机是否发生空化现象,提出了一种基于图像识别的模型水轮机多态图像智能识别方法。该方法通过机器预处理及二值化处理对目标水轮机转轮图像进行特征提取,并构造目标特征矩阵;将该目标特征矩阵与经专家库得到的修正系数或修正区间相乘后输入到空化识别模型中,并与模型中存储的模板图像的修正特征矩阵进行比对,实现模型水轮机的空化识别。工程应用结果表明:该方法的识别准确率约为80%,存在少许“错杀”现象,但可以满足使用要求;相较于现有方法,该方法不仅能提高水轮机空化识别的速度,还能提高识别质量,实现水轮机空化检测的智能化、数字化、简单化。

基于机器学习的恶意PNG图像识别方法

为避免网络病毒借助便携式网络图形(Portable Network Graphics,PNG)传播恶意代码,应用机器学习技术,提出一套行之有效的恶意PNG图像识别方法。该识别方法采用动态分析的方式,评估PNG图像和加载器行为,同时结合基于传统调用特征的机器学习算法,分类并识别恶意PNG图像。结果表明,提出的恶意PNG图像识别方法具有较高的可靠性和可行性,可以保证对多种恶意PNG图像的识别效果,还能避免用户隐写处理健康图像信息,完全符合图像水印隐秘传输应用需求。

视觉传达平面设计在构建品牌识别度中的作用研究

当今快速变化的市场环境中,视觉传达平面设计对于构建品牌识别度扮演着至关重要的角色。品牌识别度关系到消费者感知和记忆品牌,还直接影响品牌的市场竞争力和长期发展。随着市场竞争的日益激烈以及消费者偏好的快速变化,传统的视觉设计方法已经无法完全满足企业的需求。因此,探索通过视觉传达平面设计有效提升品牌识别度以及面对市场挑战时调整设计策略,成为品牌管理和市场营销研究中的重要课题。本文将系统分析视觉传达平面设计在提升品牌识别度中的作用,探讨当前设计实践中面临的主要问题,并提出相应的策略,旨在为企业提供科学的设计指导和建议,以更好地适应市场变化,优化品牌形象。

基于图形识别技术的新时代军营智慧食堂建设应用探析

军事后勤领域工作事关军队建设发展,特别是饮食供给保障从来都是影响军队战斗力生成的关键因素之一。在新时代下,利用图形识别技术探索建设智慧食堂,依托信息化系统搭建军营餐饮智慧化保障模式,可以高效精准实现军营用餐保障,科学合理提升官兵身体素质,有效促进部队战斗力生成。

电网厂站接线图人工智能识别关键方法

矢量化的电网厂站接线图需要调度运维人员参考设计图纸进行人工绘制及导入,工作量巨大且极易出错。针对电网厂站接线图中图元、文字以及接线关系3个核心的识别问题,提出一套基于人工智能的完整电网厂站接线图识别方法,显著提升识别的效率和准确性。通过结合分级预处理的重叠滑窗机制与YOLOv4算法,解决电网厂站接线图的“大图像小图元检测”问题;通过迁移学习与卷积循环神经网络结合,提升包含中文电气文本的识别率;通过嵌入电气领域知识与规则,提升接线识别的准确率。最后,根据获取的电气元件信息、文本信息、连接线信息,完成其他下游任务。采用实际调度系统导出的电网接线图数据集,设计了图元、文字、接线识别三方面的对比实验,验证了所提方法的有效性。

基于应用型人才培养的平法识图课程教学改革研究

为适应土木工程行业高质量发展的需要,契合地方普通本科高校向应用型转变的战略和决策,作为土木工程专业核心基础课程的平法识图课程也有必要进行相应的教学改革。文章结合目前地方普通本科高校在本课程教学中存在的问题,提出了基于教学改革方面的目标导向、综合实训、教学模式、考核办法等四个方面的措施。旨在丰富地方普通本科高校在平法识图课程教学改革中的研究成果,以期为同类型高校培养高素质的应用型人才和发展转型提供助力。

Urban scene recognition by graphical model and 3D geometry

This paper proposes a simple and discriminative framework, using graphical model and 3D geometry to understand the diversity of urban scenes with varying viewpoints. Our algorithm constructs a conditional random field （CRF） network using over-segmented superpixels and learns the appearance model from different set of features for specific classes of our interest. Also, we introduce a training algorithm to learn a model for edge potential among these superpixel areas based on their feature difference. The proposed algorithm gives competitive and visually pleasing results for urban scene segmentation. We show the inference from our trained network improves the class labeling performance compared to the result when using the appearance model solely.

图形相似的基本原理、方法及其在结构模式识别中的应用

将相似的有关思想和方法引入到图形识别和理解中 ,系统地讨论了图形相似的基本原理和方法 .首先分析了图形的相似性特征、相似性的内涵以及相似性的性质 ,同时给出了图形相似度的计算方法 ;其次 ,借助图的方式对图形的各相似性特征进行描述 ,并提出了统一的图形特征编码方式 ,以此实现图形由“形”到“数”的转换 ;而且 ,提出了一种具有层次性的、以图形特征编码为基础、以相似度为依据的图形相似性判别算法 ;最后 ,将该方法应用于基于二维的结构模式识别中 ,以一个实际零件中的非相交基元体的识别为例说明了该方法的具体应用 .实验结果表明 ,与传统的识别方法相比较 ,该方法在模式的识别范围、模式的搜索以及模式的匹配速度等几个方面取得了较大进展 ,并且这种基于多个相似性特征的图形识别方法具有更大的灵活性和可靠性 .

基于规则的建筑结构图钢筋用量自动识别系统

传统的手工建筑工程量统计方法不仅费时而且容易出错,利用计算机自动完成工程量统计工作则可以很好地解决这一问题.介绍了一个基于规则的建筑结构图自动识别系统（automatic interpretation of structuredrawings,简称AISD）.该系统以矢量化后的电子图档为基础,通过总结建筑工程图结构特征及绘图规则,自动分析图中的各种图形元素、符号以及其关系,理解各种部件信息,并加以综合,以获取正确的建筑工程钢筋用量.通过对工程图的特征进行详细的研究,总结出一套基于规则的适应不同类型工程图的理解方法.试验结果表明,这种方法为建筑工程图的自动识别和理解提供了一个可取的解决途径.