Active Contours and Mumford-Shah Segmentation Based on Level Sets

IntroductionThe basic idea in active contour models orsnakes is to evolve a curve,subject to constraintsfrom a given image,in order to detect objects inthat image.For instance,starting with a curvearound the object to be detected,the curve movestoward its interior normal and has to stop on theboundary of the object.LetΩ be a bounded open subset of R2 ,with Ω its boundary. Let u0 ∶Ω→ R be a given image,and C( s)∶ [0 ,1 ]→ R2 be a parameterized curve. Inthe classical snakes and active…     

梁滩河流域污染原因分析及改善措施探讨

在众多污染因素中,农业非点源污染比重最大,其次是工业点源污染,城镇化集中生活污水的影响相对较小。结合流域实际情况,提出畜禽代谢产物资源化利用、兴修污水处理厂、建造人工湿地和修筑稳定塘等改善措施,为改善梁滩河流域污染现状提供相应的参考。     

A Novel Method for Character Segmentation in Natural Scenes

Introduction Nowadays the applications of scene text recog-nition are rapidly expanding with the developmentof portable digital imaging devices[1]. However,character extraction from scene images has alwaysbeen a challenging problem due to complex back-ground, uneven illumination, shadows and noise ofimages[2]. Besides, languages also impose anotherlevel of variation in text. Characters in such lan-guages as Chinese, Japanese and Korean are usual-ly composed of several strokes, which do not n…     

基于MapInfo的城市公交查询系统的设计与实现

研究城市公交查询系统的设计与实现。利用动态分段技术,建立了基于MapInfo的动态分段数据结构,充分考虑乘客出行心理,提出了公交出行最优路径算法,设计了城市公交查询系统,实现输入查询信息或直接对地图操作来获得出行最优路线和换乘方案,提高乘客出行的便利性和高效性。     

公路服务商业化经营与企业经营行为

综合经济学和交通工程学理论,以公路服务的经营特性、市场需求和市场细分为基础,研究了公路企业的经营目标、收费价格确定方法、收费定价策略与调价方法,进而分析和得到了公路企业的经营方法。实践证明,经营方法使得公路企业的收费经营行为更为科学,增加了收费收入;公共管制方法在合理考虑企业利益的同时,能够约束公路企业的追利行为,减少社会福利损失。这对公路企业经营收费公路和政府对公路企业经营行为的管制,具有指导意义。     

细胞图像自动分割方法研究

提出一种细胞图像的自动分割与定位方法．首先将直方图分割所得二值图像的距离变换作为边缘提取的指导知识，进行细胞图像的精确分割；然后利用分割边缘点的梯度方向和几何知识确定细胞的中心．该方法既能对非重叠细胞也能对重叠细胞进行细胞的分割与定位．     

Image series segmentation and improved MC algorithm

A semiautomatic segmentation method based on active contour is proposed for computed tomography （CT） image series. First, to get initial contour, one image slice was segmented exactly by C-V method based on Mumford-Shah model. Next, the computer will segment the nearby slice automatically using the snake model one by one. During segmenting of image slices, former slice boundary, as next slice initial contour, may cross over next slice real boundary and never return to right position. To avoid contour skipping over, the distance variance between two slices is evaluated by an threshold, which decides whether to initiate again. Moreover, a new improved marching cubes （MC） algorithm based on 2D images series segmentation boundary is given for 3D image reconstruction. Compared with the standard method, the proposed algorithm reduces detecting time and needs less storing memory. The effectiveness and capabilities of the algorithm were illustrated by ,experimental results.     

A Closed Form Solution to Segment 3D Motion Using Straight-line Optical Flow

A closed form solution to the problem of segmenting multiple 3D motion models was proposed fromstraight-line optical flow. It introduced the multibody line optical flow constraint (MLOFC), a polynomial equation relating motion models and line parameters. The motion models can be obtained analytically as the derivative of the MLOFC at the corresponding line measurement, without knowing the motion model associated with that line. Experiments on real and synthetic sequences were also presented.     

一种基于MRF的多层遗传递减视频对象分割算法

提出一种视频对象分割方法,将时域信息、空域信息和图像颜色特征有效地结合起来,采用MRF遗传递减式分类来提取视频对象.利用视频帧的颜色特征,在初始分割中采用时空域分水岭方法,建立一个时空域毗连图(ST-RAG);基于时空域毗连图建立马尔可夫随机场(MRF)模型,在分割过程中采用遗传递减式方法对区域进行合理分类,利用形态学进行后处理,分割出感兴趣的视频对象.实验结果表明所获取的分割方法具有灵活性,且精度高.     

基于M形深度架构的非结构化道路可行驶区域推荐模型

针对边界模糊、路况多变的非结构化道路，为满足智能汽车在正常、应急等复杂行驶工况下对可行驶区域的视觉检测需求，提出一种在M形深度架构下融合多尺度交互策略和双重注意力机制的可行驶区域推荐模型，能够在复杂驾驶场景中精细分割出非结构化道路的强推荐、弱推荐、不推荐行驶区域。首先，在编码器-解码器的骨架基础上，构建倒金字塔式的多尺度分层输入和分层输出结构，以有效融合非结构化道路的浅层形态学特征与深层语义信息，并平衡模型在不同尺度上的预测偏倚，提升复杂驾驶场景下对多尺度与变尺度目标的分割精度；其次，构建集成通道注意力和空间注意力的跳跃连接结构，使模型在实现编码特征与解码特征高效传递的同时，聚焦于学习与道路可行驶性相关的重要特征，进一步强化模型对非结构化道路的检测性能。通过多种途径构建包含城郊、乡村、园区等真实场景的非结构化道路驾驶数据集。试验结果表明：得益于M形深度架构对多尺度交互策略和双注意力机制的融合，提出的模型在多种真实驾驶场景下均能较好地实现强推荐行驶区域、弱推荐行驶区域、不推荐行驶区域和背景区域的精细分割，平均交并比达到92.46%，平均检测速度达到22.7帧·s^-1；与现有其他主流模型相比，提出的模型兼顾了分割精度和时间效率，在非结构化道路可行驶区域检测任务上有明显优势。