Target region location based on texture analysis and active contour model

Traditional texture region location methods with Gabor features are often limited in the selection of Gabor filters and fail to deal with the target which contains both texture and non-texture parts.Thus,to solve this problem,a two-step new model was proposed.In the first step,the original features extracted by Gabor filters are applied to training a self-organizing map (SOM) neural network and a novel merging scheme is presented to achieve the clustering.A back propagation (BP) network is used as a classifier to locate the target region approximately.In the second step,Chan-Vese active contour model is applied to detecting the boundary of the target region accurately and morphological processing is used to create a connected domain whose convex hull can cover the target region.In the experiments,the proposed method is demonstrated accurate and robust in localizing target on texture database and practical barcode location system as well.     

海洋氨氧化古菌及其驱动的碳氮生物地球化学循环过程研究进展

氨氧化古菌（AOA）在海洋环境中分布广泛,是海洋水体中数量最为丰富的原核生物之一。AOA作为海洋中氨氧化作用的主导微生物,能在寡营养条件下通过化能自养的形式进行固碳,在海洋的碳、氮循环过程中发挥重要作用。AOA氨氧化过程驱动的化能自养固碳是深海内部重要能量来源,为研究深海内部有机碳输入与深海微生物群的有机碳需求之间的不平衡问题以及深海自养生物能量来源问题提供重要导向。本文对于海洋AOA的多样性分布、碳氮生物地球化学循环过程及其在海洋能量循环过程中的功能进行系统的综述,以期为本领域的研究提供借鉴。