摘要
针对现阶段特征提取方法忽视图像自身的视觉信息的问题,提出了基于图像自身复杂视觉信息的特征提取算法与应用。该算法分析了视觉皮层V1区4B层复杂细胞的视觉功能,揭示了复杂视觉细胞提取区域图像非线性、独立和平移不变性特征的能力,建立了复杂视觉细胞的数学模型,并通过该模型提取了区域图像包含的复杂视觉信息。实验证明:所提算法依据图像自身包含的高级视觉信息,自适应提取区域图像的非线性、独立性和几何不变性特征,克服了常见特征提取算法忽视图像自身视觉特征的缺陷;在基于图像内容的图像检索领域,算法取得了良好的检索效果。
Feature extraction is a key position in the field of image analysis,understanding and recognition.At the present stage,the approach of feature extraction ignores its own visual information of image.Based on that,feature extraction algorithms and applications based on the complex visual information of image itself was proposed.The algorithm analyzes the complex cells function of at the area V1 layer 4Bof visual cortex,reveals the ability of the complexity of the visual cells,i.e.extracting image region independent,non-linear and translation invariant features,creats the mathematical model of complex visual cells,and extracts complex visual information of region image.It solves the shortcomings of ignoring the visual characteristics of the image itself and achieves good search results in the field of content-based image retrieval.
出处
《计算机科学》
CSCD
北大核心
2014年第S1期234-238,共5页
Computer Science
基金
河北省高等学校科学研究项目(Z2012127)
承德市财政支撑项目(CZ2012009)
河北民族师范学院科学技术研究项目(201303)资助
关键词
视觉感知理论
几何不变性
非线性主成分分析
特征提取
Visual perception theory,Geometric invariance,Nonlinear principal component analysis,Feature extraction