Electrical Capacitance Tomography (ECT) is an image generating system based on soft field sensory system. The preferred Linear Back Projection (LPB) reconstruction algorithm for multi-phase measurement has blurring effect on the image generated. These two inherent factors, among others, affect the quality of image generated from ECT systems. Introducing fitting in the image generation process is one the solutions to improving its quality. In this article an alternative fitting mechanism based on the Gompertz function has been developed and evaluated. Comparative analysis results shows improvement on the spatial quality of images generated, in terms of minimum relative image and distribution errors, maximum correlation coefficient, and at relatively no additional computational cost. The mechanism is more effective for annular than stratified flow data hence complimenting the weakness of Xie method for annular flow.
Palm vein recognition (PVR) refers to the contactless biometric identification method that uses palm vein patterns to confirm the identity of a person. Compared with other methods, PVR has received a wide attention because it provides more secure results. The veins, being located inside the human body, make PVR robust against tempering and changes in morphology of body features. Most PVR systems integrate four stages: image acquisition, pre-processing, feature extraction, and decision. The first two stages determine accuracy of the final identification results. Focusing on the pre-processing component, we discovered that the available approaches fail to generate more informative vein patterns by simultaneously suppressing noise and blur, and also by recovering semantically useful features (edges, contours, and lines) from the acquired images. This weakness calls for sophisticated acquisition devices that make PVR systems costly. In this work, we have proposed multiframe super-resolution (MSR) as a pre-processing stage to improve performance of the traditional PVR systems. MSR exploits information from multiple images of the same scene to reconstruct a high-resolution image. This technique signals the possibility of using inexpensive low-resolution imaging devices demanded by the traditional PVR systems. Experiments show that our method outperforms most classical methods.
Since 2005, Makerere University and the University of Dar es Salaaam have taken definitive steps toward the development and utilization of iLabs. This chapter presents the iLabs experiences of the two East African universities. The experiences presented here are characterized by: institutionalization of developer teams, development of ELVIS-based iLabs, staff & student exchanges, and utilization of iLabs to support curricula. The two universities have also undertaken to setup iLabs communities at peer universities and other higher institutions of learning in East Africa.
This paper analyses the performance of grey level fitting mechanism based on Gompertz function used in Electrical Capacitance Tomography measurement system. In order to evaluate its performance, the data fitting mechanism has been applied to common image reconstruction algorithms which include; Linear Back Projection, Singular Value Decomposition, Tikhonov Regularization, Iterative Tikhonov Regularization, Landweber iteration and Projected Landweber iteration. Images were reconstructed using measured capacitance data for annular and stratified flows, and qualitative and quantitative evaluation were done on the reconstructed images in comparison with respective reference images. Results show that this grey level fitting mechanism is better in terms of improving image spatial resolution, minimizing relative image error and distribution error and maximizing correlation coefficient.
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