制作网页图片的访问 外文文献译文和原文.doc
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制作网页图片的访问 外文文献译文和原文,webinsight: making web images accessiblejeffrey p. bigham, ryan s. kaminsky, richard e. ladner, oscar m. danielsson and gordon l. hemptonabstractimages without ...
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WebInSight: Making Web Images Accessible
Jeffrey P. Bigham, Ryan S. Kaminsky, Richard E. Ladner,
Oscar M. Danielsson and Gordon L. Hempton
Abstract
Images without alternative text are a barrier to equal web access for blind users. To illustrate the problem, we conducted a series of studies that conclusively show that a large fraction of significant images have no alternative text. To ameliorate this problem, we introduce WebInSight, a system that automatically creates and inserts alternative text into web pages on-the-y. To formulate alternative text for images, we present three labeling modules based on web context analysis, enhanced optical character recognition (OCR) and human labeling. The system caches alternative text in a local database and can add new labels seamlessly after a web page is downloaded, resulting in minimal impact to the browsing experience.
Keywords
Web accessibility, web studies, transformation proxy, optical character recognition
1. INTRODUCTION
Blind users do not currently have equal access to the web. Images are used in navigation bars, as form buttons and to display textual and visual content, but, unless web authors provide alternative text for these images, blind users employing screen readers and refreshable Braille displays are left to guess the images’ contents. In our studies we found that a large fraction of images lack alternative text. For example, of the significant images found on the homepages of the 500 most high-traffic websites[1], only 39.6% were as signed alternative text.
Illustrating the problem, the homepage of the UCLA Computer Science Department (Figure 1) contains 30 images that should have alternative text, but only two (6.67%) were assigned any text at all. As a result, a blind user may have difficulty navigating this page. As another example, the University of Michigan Computer Science and Engineering Department provides a listing of all faculty on its website along with their contact information (Figure 2). Unfortunately, each e-mail address is presented as an image without equivalent alternative text, presumably in a misguided attempt to thwart e-mail harvesters1. The unintended consequence, however, is that blind users who want to e-mail these professors either cannot do so or must find their e-mail addresses through other means. The problems highlighted here are characteristic of many sites throughout the web.
WebInSight ：制作网页图片的访问
Jeffrey P. Bigham, Ryan S. Kaminsky, Richard E. Ladner,
Oscar M. Danielsson and Gordon L. Hempton
摘要
文盲可使用图象进行网页浏览。为了说明问题，我们进行了一系列的研究，得出结论表明，很大一部分重要的图像没有别的选择文本。为了改善这个问题，我们引进WebInSight ，系统会自动创建并插入替代文字到网页上的信号。制定替代文字的图片，我们提出三个模块贴标基于Web的背景分析，增强文字标识符识别（ OCR ）和人力标记。该系统缓存替代文字在当地的数据库，并可以添加新的标签后，无缝的网页下载，从而影响最小的浏览体验。
关键词
网页可读性，网络的研究，转化代理，文字标识符识别
1.导言
文盲目前没有平等地使用网页。图片中使用的导航栏，作为形式按钮和显示的文字和视觉的内容，但除非网络作者提供替代文字这些图片，文盲使用屏幕阅读器和refreshable盲文显示器左猜的图像内容。在我们的研究，我们发现，很大一部分缺乏图像替代文字。举例来说，重要的图像在网站上的500最高流量的网站[ 1 ] ，只有39.6 ％ ，分别为替代文字。
深入这个问题，加州大学洛杉矶分校计算机科学系（图1 ）包含30个影像，应该有替代图片，但只有两个（ 6.67 ％ ）被指派任何文字占全部。因此，一个盲人的用户可能会遇到困难浏览此网页。另一个例子是，美国密歇根大学计算机科学与工程系提供了一个清单，把所有教师在其网站上与他们的联系信息（图2 ） 。不幸的是，每个e-mail地址是作为一个形象不等于替代文字，大概是在误导试图阻挠电邮harvesters1 。意想不到的后果，然而，是谁盲目用户想用e - mail这些教授也不能这样做或必须找到自己的e - mail地址通过其他手段。这些问题突出的特点是这里的许多地盘整个网络。
图像，要么有一个行动与他们有联系的（例如，链接或按钮）或彩色的和大于一定规模的特别关注。当这些图像没有替代文字，可无障碍严重减少。 WebInSight系统的介绍了目标，例如signicant图像和提供了一种机制，自动插入适当的替代文字。它通过处理网络请求，并改变了返回网页上飞行。作为转变过程中，三个新的坐标，形象标识模块针对这一领域，利用方法的基础上加强网络方面的分析，光学字符识别nition （光学字符识别）和人力标记。
在本文中，我们提出了一系列的网络研究，证明所观察到的问题，讨论的架构和实施WebInSight ，并nally ，描述标记模块用于指定替代文字任意图像在..
Jeffrey P. Bigham, Ryan S. Kaminsky, Richard E. Ladner,
Oscar M. Danielsson and Gordon L. Hempton
Abstract
Images without alternative text are a barrier to equal web access for blind users. To illustrate the problem, we conducted a series of studies that conclusively show that a large fraction of significant images have no alternative text. To ameliorate this problem, we introduce WebInSight, a system that automatically creates and inserts alternative text into web pages on-the-y. To formulate alternative text for images, we present three labeling modules based on web context analysis, enhanced optical character recognition (OCR) and human labeling. The system caches alternative text in a local database and can add new labels seamlessly after a web page is downloaded, resulting in minimal impact to the browsing experience.
Keywords
Web accessibility, web studies, transformation proxy, optical character recognition
1. INTRODUCTION
Blind users do not currently have equal access to the web. Images are used in navigation bars, as form buttons and to display textual and visual content, but, unless web authors provide alternative text for these images, blind users employing screen readers and refreshable Braille displays are left to guess the images’ contents. In our studies we found that a large fraction of images lack alternative text. For example, of the significant images found on the homepages of the 500 most high-traffic websites[1], only 39.6% were as signed alternative text.
Illustrating the problem, the homepage of the UCLA Computer Science Department (Figure 1) contains 30 images that should have alternative text, but only two (6.67%) were assigned any text at all. As a result, a blind user may have difficulty navigating this page. As another example, the University of Michigan Computer Science and Engineering Department provides a listing of all faculty on its website along with their contact information (Figure 2). Unfortunately, each e-mail address is presented as an image without equivalent alternative text, presumably in a misguided attempt to thwart e-mail harvesters1. The unintended consequence, however, is that blind users who want to e-mail these professors either cannot do so or must find their e-mail addresses through other means. The problems highlighted here are characteristic of many sites throughout the web.
WebInSight ：制作网页图片的访问
Jeffrey P. Bigham, Ryan S. Kaminsky, Richard E. Ladner,
Oscar M. Danielsson and Gordon L. Hempton
摘要
文盲可使用图象进行网页浏览。为了说明问题，我们进行了一系列的研究，得出结论表明，很大一部分重要的图像没有别的选择文本。为了改善这个问题，我们引进WebInSight ，系统会自动创建并插入替代文字到网页上的信号。制定替代文字的图片，我们提出三个模块贴标基于Web的背景分析，增强文字标识符识别（ OCR ）和人力标记。该系统缓存替代文字在当地的数据库，并可以添加新的标签后，无缝的网页下载，从而影响最小的浏览体验。
关键词
网页可读性，网络的研究，转化代理，文字标识符识别
1.导言
文盲目前没有平等地使用网页。图片中使用的导航栏，作为形式按钮和显示的文字和视觉的内容，但除非网络作者提供替代文字这些图片，文盲使用屏幕阅读器和refreshable盲文显示器左猜的图像内容。在我们的研究，我们发现，很大一部分缺乏图像替代文字。举例来说，重要的图像在网站上的500最高流量的网站[ 1 ] ，只有39.6 ％ ，分别为替代文字。
深入这个问题，加州大学洛杉矶分校计算机科学系（图1 ）包含30个影像，应该有替代图片，但只有两个（ 6.67 ％ ）被指派任何文字占全部。因此，一个盲人的用户可能会遇到困难浏览此网页。另一个例子是，美国密歇根大学计算机科学与工程系提供了一个清单，把所有教师在其网站上与他们的联系信息（图2 ） 。不幸的是，每个e-mail地址是作为一个形象不等于替代文字，大概是在误导试图阻挠电邮harvesters1 。意想不到的后果，然而，是谁盲目用户想用e - mail这些教授也不能这样做或必须找到自己的e - mail地址通过其他手段。这些问题突出的特点是这里的许多地盘整个网络。
图像，要么有一个行动与他们有联系的（例如，链接或按钮）或彩色的和大于一定规模的特别关注。当这些图像没有替代文字，可无障碍严重减少。 WebInSight系统的介绍了目标，例如signicant图像和提供了一种机制，自动插入适当的替代文字。它通过处理网络请求，并改变了返回网页上飞行。作为转变过程中，三个新的坐标，形象标识模块针对这一领域，利用方法的基础上加强网络方面的分析，光学字符识别nition （光学字符识别）和人力标记。
在本文中，我们提出了一系列的网络研究，证明所观察到的问题，讨论的架构和实施WebInSight ，并nally ，描述标记模块用于指定替代文字任意图像在..
