A wide range of smartphone applications are emerging that employ image processing and computer vision algorithms to interpret the contents of images acquired by the phone's built-in camera, including applications that read product barcodes and recognize a variety of documents and other objects. However, almost all of these applications are designed for normally sighted users; a major barrier for visually impaired users (who might benefit greatly from such applications) is the difficulty of taking good-quality images. To overcome this barrier, this paper focuses on reducing the incidence of motion blur, caused by camera shake and other movements, which is a common cause of poor-quality, unusable images. We propose a simple technique for detecting camera shake, using the smartphone's built-in accelerometer (i.e. tilt sensor) to alert the user in real-time to any shake, providing feedback that enables him/her to hold the camera more steadily. A preliminary experiment with a blind iPhone user demonstrates the feasibility of the approach.
Sanketi et al. REF describe methods of anti-blur feedback for visually impaired users of Smartphone camera using the IMU sensor data.
Anti-blur feedback for visually impaired users of smartphone cameras
ASSETS '10
Computer Science Medicine