Image categorization for improving accessibility to information graphics
Image categorization for improving accessibility to information graphics
复制标题
图像分类以提高信息图形的可访问性
DOI：
--
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
K. Barner
中科院分区：
文献类型：
--
作者：
Jinglun Gao;R. Carrillo;K. Barner
信息图形是数字媒体中重要的视觉信息。本文探讨视障人士使用资讯图形时的无障碍问题。目的是向他们提供数字中所包含的全面数字信息。为了实现这一目标，我们解决了自动图形分类，信息提取和多模态表示方案的实际问题。特别地，系统使用图像处理和机器学习算法来识别图像类别。利用图像类的知识，提取特定领域的特征和信息，然后根据需要采用不同的呈现方式。本文首先提出了系统框架，然后重点介绍了自动分类算法。
Information graphics are important visual information in digital media. This paper investigates the accessibility issues associate with the information graphics for visually impaired people. The goal is to provide them with comprehensive numerical information contained in the figures. Towards the goal, we address the practical problems of automatic figure categorization, information extraction and multi-modal presentation scheme. In particular, the system identifies the image class using image processing and machine learning algorithms. With the knowledge of the image class, specific domain features and information are extracted, and then different modalities of presentation are employed based on the need. This paper first proposes the system framework and then focuses on the automated categorization algorithm.