MobileEye OCR for the Visually Impaired
MobileEye OCR for the Visually Impaired
批准号:
7053650
负责人:
HUIPING LI
金额:
$10.49万
依托单位国家:
美国
项目类别:
财政年份:
2006
资助国家:
美国
项目状态:
已结题
起止时间:
2006-05-01 至 2007-10-30
中文摘要
描述(申请人提供):在这份SBIR中,我们建议证明移动OCR的技术可行性,这是一种便携式软件系统,利用现有的个人设备为老年人或视障人士提供访问文本材料的途径。该系统将帮助这些视力低下的人进行基本的日常活动,如购物、准备食物、服药和阅读交通标志。它将超越我们建议的MobileEyes视觉增强系统,将尖端识别技术应用于移动设备。该系统将使用普通的照相手机硬件来捕获和增强文本信息,执行光学字符识别(OCR),并提供音频或视觉反馈。我们的研究将集中在有限资源的移动设备上实现和集成新的视觉增强和分析技术。具体地说,我们将开发算法来检测和纠正受透视失真影响的平面和广义柱面上的文本,实现更健壮和高效的算法和系统来稳定和增强文本块,在复杂纹理背景上提供移动OCR,并在跨各种平台的小型设备上实现这些技术。识别的文本将通过文本到语音(TTS)呈现,或以增强的质量显示在设备上,低视力用户可以轻松阅读。第一阶段将侧重于展示我们方法的技术可行性,并将纳入一种业绩衡量方法,以定量评估进展情况,并对照其他方法评估我们的系统。与现有的视力增强设备(如放大镜、望远镜和文本阅读设备,如基于扫描仪的OCR)相比,我们的解决方案具有以下几个优势:1)它使用单一的便携式设备(照相手机),该设备通常可用于电信功能;2)用户可以选择性地使用它,这样他们就不会被无关的信息淹没;3)它可以直接与其他应用程序集成,以执行专门的任务。我们的研究成果将影响数以百万计的低视力者和盲人,以及视觉和计算机视觉研究人员。我们的团队是唯一有资格探索将视觉应用扩展到这些设备的可行性的团队,并为集成未来的视觉算法提供平台。
英文摘要
DESCRIPTION (provided by applicant): In this SBIR we propose to demonstrate the technical feasibility of Mobile OCR, a portable software system which makes use of existing personal devices to provide access to textual materials for the elderly or the visually impaired. The system will help these low vision individuals with basic daily activities, such as shopping, preparing meals, taking medication, and reading traffic signs. It will step beyond our proposed MobileEyes vision enhancement system to apply cutting edge recognition technology for mobile devices. The system will use common camera phone hardware to capture and enhance textual information, perform Optical Character Recognition (OCR) and provide audio or visual feedback. Our research will focus on implementing and integrating new vision enhancement and analysis techniques on limited resource mobile devices. Specifically, we will develop algorithms for detection and rectification of text on planes and generalized cylinders subject to perspective distortions, implement more robust and efficient algorithms and systems for stabilization and enhancement of text blocks, provide mobile OCR on complex textured backgrounds, and implement these techniques on small devices across a variety of platforms. The recognized text will be presented through Text-to-Speech (TTS), or displayed on the device with enhanced quality which can be easily read by low vision users. Phase I will focus on demonstrating the technical feasibility of our approach, and will incorporate a performance measurement methodology to quantitatively evaluate progress and evaluate our system against other approaches. In comparison to existing vision enhancement devices, such as magnifying glasses, telescopes, and text reading devices such as scanner-based OCR, our solution has several advantages: 1) it makes use of a single, portable device (camera cell phone) that is commonly available and typically already carried for its telecommunications capabilities; 2) it can be used selectively by users so they will not be overwhelmed by irrelevant information; and 3) it can be integrated directly with other applications for specialized tasks. Our research results will impact the millions of low-vision individuals and the blind, as well as vision and computer vision researchers. Our team is uniquely qualified to explore the feasibility of extending visual applications to these devices, and provide a platform for integrating future vision algorithms.
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