RESUMO
A nickel-catalyzed cross-coupling reaction of aryl methyl sulfides with aryl bromides has been developed to access biaryls in yields of up to 86%. The reactions proceeded well using Ni(COD)2 as catalyst with the ligand BINAP (2,2'-bis(diphenylphosphanyl)-1,1'-binaphthalene) in the presence of magnesium. The method has a broad scope of substrates and is scalable. The wide availability of commercially available aryl bromides and the absence of preparation and preparation of organometallic reagents make the reaction of high application value.
RESUMO
Iris segmentation is an essential module in iris recognition because it defines the effective image region used for subsequent processing such as feature extraction. Traditional iris segmentation methods often involve an exhaustive search of a large parameter space, which is time consuming and sensitive to noise. To address these problems, this paper presents a novel algorithm for accurate and fast iris segmentation. After efficient reflection removal, an Adaboost-cascade iris detector is first built to extract a rough position of the iris center. Edge points of iris boundaries are then detected, and an elastic model named pulling and pushing is established. Under this model, the center and radius of the circular iris boundaries are iteratively refined in a way driven by the restoring forces of Hooke's law. Furthermore, a smoothing spline-based edge fitting scheme is presented to deal with noncircular iris boundaries. After that, eyelids are localized via edge detection followed by curve fitting. The novelty here is the adoption of a rank filter for noise elimination and a histogram filter for tackling the shape irregularity of eyelids. Finally, eyelashes and shadows are detected via a learned prediction model. This model provides an adaptive threshold for eyelash and shadow detection by analyzing the intensity distributions of different iris regions. Experimental results on three challenging iris image databases demonstrate that the proposed algorithm outperforms state-of-the-art methods in both accuracy and speed.
