【摘要】 为了在随身行李X光图像中自动地检测和识别低亮度的危险物品,首先需要将原始图像进行分割,以得到各个目标的区域.分割图像既不能过分割,也不能欠分割.本文提出了一种基于投影的X光图像分割区域数量判定方法,通过比较分割图像序列在水平和垂直方向投影的相关程度的变化,确定最佳的图像分割区域数量.和基于统计有效指数的方法相比,该方法综合考虑了图像的统计信息和空间分布信息,不仅所得到的最优分割图像中包含足够的目标信息,便于后续的目标检测和识别,而且算法具有较小的计算量.更多还原

【Abstract】 Automatic detection of low intensity threat objects in the x ray image of carry on luggage requires firstly segmenting the x ray image into a number of object regions. The segmented image should contain sufficient objects, neither over segmented nor less segmented. In general, the optimal number of regions is not known in advance. The widely used statistical validity index methods can not give satisfactory estimation of the optimal number of regions because they do not consider the spatial information of the image. A novel method for determining the optimal number of image segmentation regions by using image projection is proposed. The new method uses the correlation between both the horizontal and vertical projections of consecutive segmented images to determine the optimal region number in the segmented image. Its advantage over the statistical validity index methods is that it utilizes both the statistical and spatial information of the image. Experiment results show that the proposed method produces segmented image with sufficient object information and has low computational requirement.更多还原