Optical flow estimation via steered-L1 norm

Global variational methods for estimating optical flow are among the best performing methods due to the subpixel accuracy and the ‘fill-in’ effect they provide. The fill-in effect allows optical flow displacements to be estimated even in low and untextured areas of the image. The estimation of such displacements are induced by the smoothness term. The L1 norm provides a robust regularisation term for the optical flow energy function with a very good performance for edge-preserving. However this norm suffers from several issues, among these is the isotropic nature of this norm which reduces the fill-in effect and eventually the accuracy of estimation in areas near motion boundaries. In this paper we propose an enhancement to the L1 norm that improves the fill-in effect for this smoothness term. In order to do this we analyse the structure tensor matrix and use its eigenvectors to steer the smoothness term into components that are ‘orthogonal to’ and ‘aligned with’ image structures. This is done in primal-dual formulation. Results show a reduced end-point error and improved accuracy compared to the conventional L1 norm

A review of hough transform and line segment detection approaches

In a wide range of image processing and computer vision problems, line segment detection is one of the most critical challenges. For more than three decades researchers have contributed to build more robust and accurate algorithms with faster performance. In this paper we review the main approaches and in particular the Hough transform and its extensions, which are among the most well-known techniques for the detection of straight lines in a digital image. This paper is based on extensive practical research and is organised into two main parts. In the first part, the HT and its major research directions and limitations are discussed. In the second part of the paper, state-of-the-art line segmentation techniques are reviewed and categorized into three main groups with fundamentally distinctive characteristics. Their relative advantages and disadvantages are compared and summarised in a table

Functional Analysis of the Cathepsin-Like Cysteine Protease Genes in Adult Brugia malayi Using RNA Interference

Filarial nematodes are an important group of human pathogens, causing lymphatic filariasis and onchocerciasis, and infecting around 150 million people throughout the tropics with more than 1.5 billion at risk of infection. Control of filariasis currently relies on mass drug administration (MDA) programs using drugs which principally target the microfilarial life-cycle stage. These control programs are facing major challenges, including the absence of a drug with macrofilaricidal or permanent sterilizing activity, and the possibility of the development of drug-resistance against the drugs available. Cysteine proteases are essential enzymes which play important roles in a wide range of cellular processes, and the cathepsin-like cysteine proteases have been identified as potential targets for drug or vaccine development in many parasites. Here we have studied the function of several of the cathepsin-like enzymes in the filarial nematode, B. malayi, and demonstrate that these cysteine proteases are involved in the development of embryos, show similar functions to their counterparts in C. elegans, and therefore, provide an important target for future drug development targeted to eliminate filariasis

Attacks on an ISO/IEC 11770-2 key establishment protocol

This paper demonstrates that two types of serious attack (replay and type) are possible on an ISO/IEC server-based key establishment protocol. The flaw is associated with the method used to ensure the freshness of an established key. Two possible solutions are proposed to deal with the identified weakness. This is of great potential impact and as a result of this work, ISO published a technical corrigendum (ISO/IEC 11770-2:1996/Cor 1:2005) to remove the protocol from ISO/IEC 11770-2: 1996

Local-global optical flow for image registration agents

Registration is a fundamental task in image processing used to match two or more images taken, for example, at different times, from different sensors, or from different viewpoints. Optical flow is a technique in computer vision area to compute the displacement field of the contents within an image sequence. In the sense of correspondence, image registration and optical flow have very close relation. On the one hand, optical flow is used to do image registration; on the other hand, it is also used to evaluate the performance of image registration. In literature, either local optical flow or global optical flow is studied for image registration. In this paper, an improved optical flow technique, namely Local-Global, which combines the advantages of both techniques, is applied for image registration. Experiments are conducted to demonstrate the effectiveness of this method