Theoretical foundation of the intersecting cortical model and its use for change detection of aircraft, cars, and nuclear explosion tests
Theoretical foundation of the intersecting cortical model and its use for change detection of aircraft, cars, and nuclear explosion tests
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DOI：
10.1016/j.sigpro.2004.03.012
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发表时间：
2004-07-01
影响因子：
4.4
通讯作者：
Kinser, JM
中科院分区：
文献类型：
--
作者：
Ekblad, U;Kinser, JM
交叉皮层模型（ICM）是一种基于神经网络技术的图像处理模型。它源自于几个视觉皮层模型，基本上是这些模型的交叉点，即这些模型之间的共同元素。给出了ICM的理论基础，并在Eckhorn和Reitboeck提出的模型的基础上，将ICM推导为脉冲耦合神经网络的简化方程组，给出了ICM的实验结果：一个是在空中飞行的飞机图像序列上的实验，两个是在汽车检测上的实验，两个是在汽车检测上的实验，两个是在汽车检测上的实验。本文通过几个例子说明了ICM在图像变化检测中的作用：飞机在均匀背景下运动，没有精确的几何匹配;两辆汽车在没有精确几何匹配的城市环境中移动;以及复杂背景中的线性结构。当运动物体不太小，背景不太困难时，可以使用ICM。即使背景不均匀，也可以检测到涉及较大线性结构的变化。(C)2004 Elsevier B. V.保留所有权利。
The intersecting cortical model (ICM) is a model based on neural network techniques especially designed for image processing. It was derived from several visual cortex models and is basically the intersection of these models, i.e. the common elements amongst these models. The theoretical foundation of the ICM is given and it is shown how the ICM can be derived as a reduced set of equations of the pulse-coupled neural network based upon models proposed by Eckhorn and Reitboeck.Tests of the ICM are presented: one on a series of images of an aircraft moving in the sky; two on car detection; and one on preparations of underground nuclear explosions.The ICM is shown here, in a few examples, to be useful in imagery change detection: aircraft moving against a homogeneous background without precise geometric matching; car on a road; two cars moving in an urban setting without precise geometric matching; and for a linear structure in a complex background. The ICM can be used when the moving objects are not too small and the background is not too difficult. Changes involving larger linear structures can be detected even if the background is not homogeneous. (C) 2004 Elsevier B.V. All rights reserved.