People who are blind or visually impaired face difficulties using a growing array of everyday appliances because they are equipped with inaccessible electronic displays. We report developments on our "Display Reader" smartphone app, which uses computer vision to help a user acquire a usable image of a display and have the contents read aloud, to address this problem. Drawing on feedback from past and new studies with visually impaired volunteer participants, as well as from blind accessibility experts, we have improved and simplified our user interface and have also added the ability to read seven-segment digit displays. Our system works fully automatically and in real time, and we compare it with general-purpose assistive apps such as Be My Eyes, which recruit remote sighted assistants (RSAs) to answer questions about video captured by the user. Our discussions and preliminary experiment highlight the advantages and disadvantages of fully automatic approaches compared with RSAs, and suggest possible hybrid approaches to investigate in the future.

People who are blind or visually impaired face difficulties accessing a growing array of everyday appliances, needed to perform a variety of daily activities, because they are equipped with electronic displays. We are developing a "Display Reader" smartphone app, which uses computer vision to help a user acquire a usable image of a display, to address this problem. The current prototype analyzes video from the smartphone's camera, providing real-time feedback to guide the user until a satisfactory image is acquired, based on automatic estimates of image blur and glare. Formative studies were conducted with several blind and visually impaired participants, whose feedback is guiding the development of the user interface. The prototype software has been released as a Free and Open Source (FOSS) project.

Modern household appliances, such as microwave ovens and DVD players, increasingly require users to read an LED or LCD display to operate them, posing a severe obstacle for persons with blindness or visual impairment. While OCR-enabled devices are emerging to address the related problem of reading text in printed documents, they are not designed to tackle the challenge of finding and reading characters in appliance displays. Any system for reading these characters must address the challenge of first locating the characters among substantial amounts of background clutter; moreover, poor contrast and the abundance of specular highlights on the display surface - which degrade the image in an unpredictable way as the camera is moved - motivate the need for a system that processes images at a few frames per second, rather than forcing the user to take several photos, each of which can take seconds to acquire and process, until one is readable.We describe a novel system that acquires video, detects and reads LED/LCD characters in real time, reading them aloud to the user with synthesized speech. The system has been implemented on both a desktop and a cell phone. Experimental results are reported on videos of display images, demonstrating the feasibility of the system.

The authors used superposition coding as opposed to the more standard random binning approach to wire-tap channels.

Most camera-based systems for finding and reading barcodes are designed to be used by sighted users (e.g. the Red Laser iPhone app), and assume the user carefully centers the barcode in the image before the barcode is read. Blind individuals could benefit greatly from such systems to identify packaged goods (such as canned goods in a supermarket), but unfortunately in their current form these systems are completely inaccessible because of their reliance on visual feedback from the user.To remedy this problem, we propose a computer vision algorithm that processes several frames of video per second to detect barcodes from a distance of several inches; the algorithm issues directional information with audio feedback (e.g. "left," "right") and thereby guides a blind user holding a webcam or other portable camera to locate and home in on a barcode. Once the barcode is detected at sufficiently close range, a barcode reading algorithm previously developed by the authors scans and reads aloud the barcode and the corresponding product information. We demonstrate encouraging experimental results of our proposed system implemented on a desktop computer with a webcam held by a blindfolded user; ultimately the system will be ported to a camera phone for use by visually impaired users.

The general Gaussian multiple-access wiretap channel (GGMAC-WT) and the Gaussian two-way wiretap channel (GTW-WT) are considered. In the GGMAC-WT, multiple users communicate with an intended receiver in the presence of an eavesdropper who receives their signals through another GMAC. In the GTW-WT, two users communicate with each other over a common Gaussian channel, with an eavesdropper listening through a GMAC. A secrecy measure that is suitable for this multiterminal environment is defined, and achievable secrecy rate regions are found for both channels. For both cases, the power allocations maximizing the achievable secrecy sum rate are determined. It is seen that the optimum policy may prevent some terminals from transmission in order to preserve the secrecy of the system. Inspired by this construct, a new scheme cooperative jamming is proposed, where users who are prevented from transmitting according to the secrecy sum rate maximizing power allocation policy ldquojamrdquo the eavesdropper, thereby helping the remaining users. This scheme is shown to increase the achievable secrecy sum rate. Overall, our results show that in multiple-access scenarios, users can help each other to collectively achieve positive secrecy rates. In other words, cooperation among users can be invaluable for achieving secrecy for the system.

We consider the Gaussian multiple access wire-tap channel (GMAC-WT). In this scenario, multiple users communicate with an intended receiver in the presence of an intelligent and informed wire-tapper who receives a degraded version of the signal at the receiver. We define suitable security measures for this multiaccess environment. Using codebooks generated randomly according to a Gaussian distribution, achievable secrecy rate regions are identified using superposition coding and time-division multiple access (TDMA) coding schemes. An upper bound for the secrecy sum-rate is derived, and our coding schemes are shown to achieve the sum capacity. Numerical results are presented showing the new rate region and comparing it with the capacity region of the Gaussian multiple-access channel (GMAC) with no secrecy constraints, which quantifies the price paid for secrecy.

We consider two-way wire-tap channels, where two users are communicating with each other in the presence of an eavesdropper, who has access to the communications through a multiple-access channel. We find achievable rates for two different scenarios, the Gaussian two-way wire-tap channel, (GTW-WT), and the binary additive two-way wire-tap channel, (BATW- WT). It is shown that the two-way channels inherently provide a unique advantage for wire-tapped scenarios, as the users know their own transmitted signals and in effect help encrypt the other user's messages, similar to a one-time pad. We compare the achievable rates to that of the Gaussian multiple-access wiretap channel (GMAC-WT) to illustrate this advantage.

We consider the Gaussian multiple access wire-tap channel (GMAC-WT). In this scenario, multiple users communicate with an intended receiver in the presence of an intelligent and informed wire-tapper who receives a degraded version of the signal at the receiver. We define a suitable security measure for this multi-access environment. We derive an outer bound for the rate region such that secrecy to some pre-determined degree can be maintained. We also find, using Gaussian codebooks, an achievable such secrecy region. Gaussian codewords are shown to achieve the sum capacity outer bound, and the achievable region coincides with the outer bound for Gaussian codewords, giving the capacity region when inputs are constrained to be Gaussian. We present numerical results showing the new rate region and compare it with that of the Gaussian multiple-access channel (GMAC) with no secrecy constraints