Locating deciduous trees

N. Haering, Z. Myles, N. da Vitoria Lobo
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引用次数: 19

Abstract

Presents a method to obtain information about the presence of deciduous trees in images. Since a single measure, observation or model is unlikely to yield robust recognition of trees, we present an approach that combines color measures and estimates of the complexity, structure, roughness and directionality of the image based on entropy measures, grey-level co-occurrence matrices, Fourier transforms, multi-resolution Gabor filter sets, steerable filters and the fractal dimension. A standard backpropagation neural network is used to arbitrate between the different measures and to find a set of robust and mutually consistent “tree experts”
定位落叶树的
提出了一种获取图像中落叶树存在信息的方法。由于单一测量、观察或模型不太可能产生对树木的鲁棒识别,我们提出了一种方法,该方法结合了颜色测量和基于熵测量、灰度共现矩阵、傅立叶变换、多分辨率Gabor滤波器集、可转向滤波器和分形维数的图像的复杂性、结构、粗糙度和方向性的估计。使用标准的反向传播神经网络在不同的度量之间进行仲裁,并找到一组鲁棒且相互一致的树专家。
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