产品理念是产品形象的核心部分

通过对产品形象设计的研究,阐述了在汽车全方位设计中,如何建立产品的品质形象和视觉形象,并制定出产品形象设计指南,最终建立自己特定的设计风格,并逐步树立起企业的品牌形象。把产品的视觉形象的设计与产品理念完美的结合起来,体现产品理念是产品形象的核心部分的思想。     

高校CIS战略与高职院校形象塑造研究

在当今高职院校面临竞争日趋激烈的环境下,CIS战略导入高职院校对塑造良好鲜明的学校形象具有重要的战略意义.本文论述了CIS战略对高职院校形象塑造的意义,分析了高校CIS战略的构成要素,提出了高职院校导入CIS战略的实施流程. 1 CIS战略对高职院校形象塑造的意义 CIS(Corporate Identity System),即“企业识别系统”或“形象识别系统”,是企业进行形象策划、设计、传播和管理的一种战略、方案和手段.其意义在于运用视觉设计,将企业的理念和特质予以视觉化、规格化及系统化.CIS包括理念识别系统(Mind Identity System,简称MIS)、行为识别系统(Behavior Identity System,简称BIS)、视觉识别系统(Vision Identity System,简称VIS)三个部分.     

企业形象设计标准色的适合性研究

企业标准色是视觉形象设计中的关键要素,在企业形象推广中具有不可替代的作用。文章从标准色的情感、心理感应和适合性等方面进行分析,探索在视觉形象设计中最具表现力的标准色,使标准色的应用表达更为准确。     

象征图案打造VI设计的纵贯线

VI(视觉识别),它是一种在企业经营理念,战略范围和经营目标的支配下,运用视觉传达方法,通过企业识别的符号来展示企业独特形象的设计系统。视觉识别系统的作用,要分为基础和应用两大部分。因为视觉识别系统是企业形象的直接传达系统。在整个VI当中,象征图案有"绿叶"之作用,同时,象征图案也是对品牌更形象的诠释,可以让受众更容易理解企业的形象识别系统。所以象征图案在VI中的地位相当重要。     

符号的自律——浅析CIS设计的认知功能及其社会意义

CIS设计的基础是视觉识别系统(Visual Identity System),它透过一切可见的视觉符号,对外传达企业经营理念与情报信息,是企业识别中最具传播力与感染力、所接触的层面最广泛、效果最直接的方面。本文主要以标志为主要载体的企业形象传播系统为基点,从视觉符号、心理认知等方面着手,简要阐述了CIS设计的认知功能及其社会意义。     

辅助图形在品牌形象再设计中应用与表现

辅助图形是企业视觉形象的组成要素之一,在品牌形象升级中起着重要的作用。文章以近年来品牌形象升级案例为研究对象,以满足品牌诉求为前提,从平面美学、色彩构成、心理学等角度进行思考,为辅助图形的再设计提供一些新思路,同时更多的关注品牌视觉形象设计与人的关系,从而使品牌理念得以更好的传达。     

宋文、葛美芹作品

正设计说明:本作品服务于美国一家亲子活动中心,品牌形象设计理念要表现海鱼形象,组成一家三口,溅起的水花,生动活泼,体现亲子之间和谐互洋,亲子,互动、和谐等元素。整体形象的视觉设计采用卡通化的鲨动,其乐融融,突出企业经营理念以及服务内容。     

论CI形象视觉元素中标志的适应性探究

标志的适应性是时代进步与发展的体现;标志作为CI企业形象的视觉系统中基础要素的核心部分并起着举足轻重的作用;探究标志的适应性策略,以保证企业形象设计的成功,避免出现不适于CI企业形象的标志;另外,企业标志形态与企业名称字体的组合形态的"友好与和谐",是CI视觉形象应用设计版面达到视觉平衡的重要因素,其标志设计的好坏将直接制约版面的视觉效果,影响着标志的适应性。     

滴滴出行品牌形象视觉传达的设计应用

品牌是企业缔造多元文化的力量,同时也是企业塑造产品的灵魂。网络格局多元化的今天,品牌视觉传达的表现不再局限于传统图案,新视觉元素的出现,强化了品牌形象定位与构成要素及创新理念。文章研究滴滴出行品牌的定位,并对其标志抽象化所带来的视觉表现以及视觉形象传播途径进行探讨。     

杭州部分老字号企业视觉形象现状的调查与分析

杭州老字号的发展见证了杭州城市发展的历史,从设计学角度关注和研究杭州老字号企业是一个有价值的研究方向,也是目前设计学界关注比较少的一个方面。本文通过对杭州老字号视觉形象的调查与分析,认为杭州老字号视觉形象资源丰富,但也存在着视觉形象管理散乱、缺乏品牌个性、品牌形象老化、品牌传播投入不足等问题。     

Learning group-based dictionaries for discriminative image representation

Dictionary learning is a critical issue for achieving discriminative image representation in many computer vision tasks such as object detection and image classification. In this paper, a new algorithm is developed for learning discriminative group-based dictionaries, where the inter-concept (category) visual correlations are leveraged to enhance both the reconstruction quality and the discrimination power of the group-based discriminative dictionaries. A visual concept network is first constructed for determining the groups of visually similar object classes and image concepts automatically. For each group of such visually similar object classes and image concepts, a group-based dictionary is learned for achieving discriminative image representation. A structural learning approach is developed to take advantage of our group-based discriminative dictionaries for classifier training and image classification. The effectiveness and the discrimination power of our group-based discriminative dictionaries have been evaluated on multiple popular visual benchmarks.     

利用频繁模式挖掘进行图像标注

在基于内容的图像检索与计算机视觉研究领域中,如何将底层的视觉特征与高层的语义信息相联系,即如何有效地根据图像的底层特征提取其表达的语义概念是备受关注的难题之一。特别是当图像包含了多个语义概念时,问题就变得更为棘手了。本文中,我们提出一种基于图像底层特征值频繁模式的语义概念标注方法,针对图像分块的特点实现了一组有效的模式挖掘算法,并设计了标注规则的生成算法。权威的真实数据集上的实验表明我们的方法在对含有多个语义概念的图像进行概念标注时要比之前的一些算法效果更好。     

Intelligent control of a robot manipulator by visual feedback

We present a new approach to visual feedback control using image-based visual servoing with stereo vision. In order to control the position and orientation of a robot with respect to an object, a new technique is proposed using binocular stereo vision. The stereo vision enables us to calculate an exact image Jacobian not only at around a desired location, but also at other locations. The suggested technique can guide a robot manipulator to the desired location without needing such a priori knowledge as the relative distance to the desired location or a model of the object, even if the initial positioning error is large. We describes a model of stereo vision and how to generate feedback commands. The performance of the proposed visual servoing system is illustrated by a simulation and by experimental results, and compared with the conventional method for an assembling robot. This work was presented in part at the Fourth International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–22, 1999     

A human vision based computational model for chromatic texturesegregation

We have developed a computational model for texture perception which has physiological relevance and correlates well with human performance. The model attempts to simulate the visual processing characteristics by incorporating mechanisms tuned to detect luminance-polarity, orientation, spatial frequency and color, which are characteristic features of any textural image. We obtained a very good correlation between the model's simulation results and data from psychophysical experiments with a systematically selected set of visual stimuli with texture patterns defined by spatial variations in color, luminance, and orientation. In addition, the model predicts correctly texture segregation performance with key benchmarks and natural textures. This represents a first effort to incorporate chromatic signals in texture segregation models of psychophysical relevance, most of which have treated grey-level images so far. Another novel feature of the model is the extension or the concept of spatial double opponency to domains beyond color, such as orientation and spatial frequency. The model has potential applications in the areas of image processing, machine vision and pattern recognition, and scientific visualization.     

基于图象分割的机器人视觉系统的设计与实现

机器人视觉系统是自主机器人的重要组成部分，而如何精确高效的处理视觉信息是视觉系统的关键问题．本文介绍了一个包括离线颜色分析器和实时视觉信息处理器两大部分的机器人视觉系统。离线颜色分析器用于提取各种颜色的阈值，实时视觉信息处理器则利用阈值进行图象分割，从而使机器人准确认知当前环境。     

一种基于视觉兴趣性的图象质量评价方法

图象质量的正确评价是图象信息工程领域内一项很有意义的研究课题,但现有的图象客观评价方法并不完全符合人眼视觉特性。合理地评价图象质量应充分遵循人眼的视觉特性,但由于受到人的心理、文化背景、周围环境、不同的应用场合等多种因素的影响,人眼对同一幅图象中的不同区域往往具有不同的感兴趣程度,即人眼具有视觉兴趣性特性,该文在充分利用视觉兴趣性特性的基础上,针对只存在一个感兴趣区的图象,提出了一种简化的图象质量     

机器视觉技术研究进展及展望

摘 要：机器视觉是建立在计算机视觉理论工程化基础上的一门学科,涉及到光学成像、 视觉信息处理、人工智能以及机电一体化等相关技术。随着我国制造业的转型升级与相关研究 的不断深入,机器视觉技术凭借其精度高、实时性强、自动化与智能化程度高等优点,成为了 提升机器人智能化的重要驱动力之一,并被广泛应用于工业生产、农业以及军事等各个领域。 在广泛查阅相关文献之后,针对近十多年来机器视觉相关技术的发展与应用进行分析与总结, 旨在为研究学者与工程应用人员提供参考。首先,总结了机器视觉技术的发展历程、国内外的 机器视觉发展现状;其次,重点分析了机器视觉系统的核心组成部件、常用视觉处理算法以及 当前主流的机器视觉工业软件;然后,介绍了机器视觉技术在产品瑕疵检测、智能视频监控分 析、自动驾驶与辅助驾驶与医疗影像诊断等 4 个典型领域的应用;最后分析了当前机器视觉技 术所面临的挑战,并对其未来的发展趋势进行了展望,为机器视觉技术的发展和应用推广发挥 积极作用。     

Design and application of industrial machine vision systems

In this paper, the role and importance of the machine vision systems in the industrial applications are described. First understanding of the vision in terms of a universal concept is explained. System design methodology is discussed and a generic machine vision model is reported. Such a machine includes systems and sub-systems, which of course depend on the type of applications and required tasks. In general, expected functions from a vision machine are the exploitation and imposition of the environmental constraint of a scene, the capturing of the images, analysis of those captured images, recognition of certain objects and features within each image, and the initiation of subsequent actions in order to accept or reject the corresponding objects. After a vision system performs all these stages, the task in hand is almost completed. Here, the sequence and proper functioning of each system and sub-systems in terms of high-quality images is explained. In operation, there is a scene with some constraint, first step for the machine is the image acquisition, pre-processing of image, segmentation, feature extraction, classification, inspection, and finally actuation, which is an interaction with the scene under study. At the end of this report, industrial image vision applications are explained in detail. Such applications include the area of automated visual inspection (AVI), process control, parts identification, and important role in the robotic guidance and control. Vision developments in manufacturing that can result in improvements in the reliability, in the product quality, and enabling technology for a new production process are presented. The key points in design and applications of a machine vision system are also presented. Such considerations can be generally classified into the six different categories such as the scene constraints, image acquisition, image pre-processing, image processing, machine vision justification, and finally the systematic considerations. Each aspect of such processes is described here and the proper condition for an optimal design is reported.     

机器人插件作业的视觉导引方法研究

插件作业（parts mating）是装配机器人的一项基本作业环节．本文介绍了以双目立体视觉 实现该作业的视觉导引方法．该方法通过采用人机交互方式,借助于人的智慧,提高了图像 特征提取和匹配的准确性和可靠性、可直观准确地给出插件作业的动作参数,克服了自动视 觉计算复杂、鲁棒性差的缺点,适用于机器人遥操作作业．实验表明,基于人机交互的机器 人插件作业在立体视觉导引下是完全可行的．