A vast number of e-voting schemes including mix-net-based e-voting, homomorphic e-voting, blind signature-based e-voting, blockchain-based e-voting, post-quantum e-voting, and hybrid e-voting have been proposed in the literature for better security and practical implementation. In this paper, we review various e-voting approaches to date. We first compare the structures, advantages, and disadvantages of the different e-voting approaches. We then summarise the security properties of the e-voting approaches in terms of their functional requirements and security requirements. In addition, we provide a comprehensive review of various types of e-voting approaches in terms of their security properties, underlying tools, distinctive features, and weaknesses. We also discuss some practical considerations in the design of e-voting systems. Subsequently, some potential research directions are suggested based on our observations.
Summary: Detection of cracks from stainless steel pipe images is done using contrast stretching technique. The technique is based on an image filter technique through mathematical morphology that can expose the cracks. The cracks are highlighted and noise removal is done efficiently while still retaining the edges. An automated crack detection system with a camera platform has been successfully implemented. We compare crack extraction in terms of quality measures with those of Otsu's threshold technique and the another technique (Iyer and Sinha, 2005). The algorithm shown is able to achieve good results and perform better than these other techniques. SCANNING 00: 1-13, 2012. C 2012 Wiley Periodicals, Inc.
This paper introduces the Contrast EnhancementBilateral Closing Top-hat Otsu Thresholding (CEBITOT) technique to perform crack detection. This technique is based on the mathematical morphology and image filtering technique to extract the crack like patterns. Mathematical morphology highlights the cracks clearly while bilateral filtering filters out the noise from the image efficiently and preserving the edges. The performance of the proposed estimator is compared with two existing methods: Otsu method, Iyer* and Sinha method over several images. The performance of the CEBITOT is significantly greater than that of the two methods.
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