Image segmentation by level set evolution with region consistency constraint

Image segmentation is a key and fundamental problem in image processing,computer graphics,and computer vision.Level set based method for image segmentation is used widely for its topology flexibility and proper mathematical formulation.However,poor performance of existing level set models on noisy images and weak boundary limit its application in image segmentation.In this paper,we present a region consistency constraint term to measure the regional consistency on both sides of the boundary,this term defines the boundary of the image within a range,and hence increases the stability of the level set model.The term can make existing level set models significantly improve the efficiency of the algorithms on segmenting images with noise and weak boundary.Furthermore,this constraint term can make edge-based level set model overcome the defect of sensitivity to the initial contour.The experimental results show that our algorithm is efficient for image segmentation and outperform the existing state-of-art methods regarding images with noise and weak boundary.

Uniformly Most Powerful Invariant Test and Its Application

The authors consider the uniformly most powerful invariant test of the testing problems (Ⅰ) H 0: μ′Σ -1 μ≥CH 1: μ′Σ -1 μ<C and (Ⅱ) H 00 : β′X′Xβσ 2≥CH 11 : β′X′Xβσ 2<C under m dimensional normal population N m(μ, Σ) and normal linear model (Y, Xβ, σ 2) respectively. Furthermore, an application of the uniformly most powerful invariant test is given.

Pedigree analysis of nationally approved soybean cultivars from 1984 to 2013 and implications for breeding

To reveal origins of 316 state authorized varieties from 1984 to 2013, rules of their parentsJ selection including types and hybrid configurations of direct parents, geo-graphical sources and types of their ancestors were analyzed. Various important direct parents and ancestors were summarized and nuclear contribution of ancestors was also estimated by pedigree analysis. Among 316 registered cultivars, 298 （94.3%） were bred by hybridization, and most of their direct parents were cultivars or breeding lines （65.5%）. Cultivars and breeding lines were mostly used as female parents, with 53.0% and 38.7% respectively. The 316 released cultivars were traced to 373 final ancestors, mainly com-posed of landraces （55.5%） and breeding lines （36.7%）. The 373 final ancestors came from different regions, including 121 from northern area, 110 from Huang-Huai-Hai area, 53 from southern area and 76 from abroad. These ancestors were mainly from the same ecologic zone as the approved cultivars. Newly approved cultivars always have more ancestors and a broader genetic base. However, distribution of these ancestors was unbalanced, and a few ancestors provided significant genetic contributions to later generations, such as the most concentrated final ancestors from Huang-Huai-Hai region followed by northern and southern regions. These results offer more information regarding their important parents and provide valuable references to soybean breeding. We should increase soybean germplasm exchanges with different regions and make use of elite lines, foreign cultivars and wild soybean germplasm to broaden the genetic background.

Simultaneous Optimality of LSE and ANOVA Estimate in General Mixed Models

Problems of the simultaneous optimal estimates and the optimal tests in general mixed models are considered. A necessary and sufficient condition is presented for the least squares estimate of the fixed effects and the analysis of variance （Hendreson III＇s） estimate of variance components being uniformly minimum variance unbiased estimates simultaneously. This result can be applied to the problems of finding uniformly optimal unbiased tests and uniformly most accurate unbiased confidential interval on parameters of interest, and for finding equivalences of several common estimates of variance components.