Browsing by Author "Rajakaruna, N"

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Embargo
Alignment parameter calibration for IMU using the Taguchi method for image deblurring
(Elsevier, 2015-04-01) Chan, K.Y; Rajakaruna, N; Engelke, U; Murray, I; Abhayasinghe, N
Inertial measurement units (IMUs) utilized in smartphones can be used to detect camera motion during exposure, in order to improve image quality degraded with blur through long hand-held exposure. Based on the captured camera motion, blur in images can be removed when an appropriate deblurring filter is used. However, two research issues have not been addressed: (a) the calibration of alignment parameters for the IMU has not been addressed. When inappropriate alignment parameters are used for the IMU, the camera motion would not be captured accurately and the deblurring effectiveness can be downgraded. (b) Also selection of an appropriate deblurring filter correlated with the image quality has still not been addressed. Without the use of an appropriate deblurring filter, the image quality could not be optimal. This paper proposes a systematic method, namely the Taguchi method, which is a robust and systematic approach for designing reliable and high-precision devices, in order to perform the alignment parameter calibration for the IMU and filter selection. The Taguchi method conducts a small number of systematic experiments based on orthogonal arrays. It studies the impact of the alignment parameters and appropriate deblurring filter, which attempts to perform an effective deblurring. Several widely adopted image quality metrics are used to evaluate the deblurred images generated by the proposed Taguchi method. Experimental results show that the quality of deblurred images achieved by the proposed Taguchi method is better than those obtained by deblurring methods which are not involved with the alignment parameter calibration and filter selection. Also, much less computational effort is required by the Taguchi method when comparing with the commonly used optimization methods for determining alignment parameters and deblurring filter.
Embargo
Inertial data based deblurring for vision impaired navigation
(IEEE, 2014-10-27) Rajakaruna, N; Rathnayake, C; Abhayasinghe, N; Murray, I
Image stabilization is very important in vision based indoor/outdoor navigation systems. Blurring is one main cause of poor image quality, which can be caused by a movement of the camera at the time of taking the image, a movement of objects in front, atmospheric turbulence or out-of-focus. Out of these factors, camera movement is dominant in navigation systems as the camera is continuously moving. This paper presents the preliminary results of deblurring performed using point spread function (PSF) computed using synchronized inertial sensor data. It uses data of the accelerometer and gyroscope to derive a motion vector calculated from the motion of the smartphone during the image capturing period. This motion vector is applied to the captured image so that the effect of motion is reversed during the debrurring process. This work is a part of an indoor navigation project that aims to assist people with vision impairment. Image processing form a significant part of the proposed system and as such clearly defined edges are essential for path and obstruction identification. Different deblurring methods are compared for their performance in reversing the effect of camera movement. Results indicated that deblurring can be successfully performed using the motion vector and that the resulting images can be used as a readily approach to object and path identification in vision based navigation systems, especially for blind and vision impaired indoor/outdoor navigation. The paper also proposes a novel deblurring algorithm that uses PSF computed for different portions of the image to deblur that portion of the image.