基于希尔伯特变换的图像边缘检测与分割

ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing Pub Date : 1988-04-11 DOI:10.1109/ICASSP.1988.196801

Gerassimos M. Livadas, A. Constantinides

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引用次数: 17

摘要

提出了一种基于两阶段过程的高效边缘检测模型。第一阶段包括对人工创建的信号进行线性变换，该信号具有检测步进边缘的特性，而不考虑两个连续边缘之间的间隔分布。结果表明，希尔伯特变换不仅具有这一特性，而且在存在噪声的阶跃边缘检测中也优于导数运算。第二阶段包括将过滤结果适当地映射到边缘检测原语。通过算例对所得结果进行了验证。

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Image edge detection and segmentation based on the Hilbert transform

An efficient edge detection model based on a two-stage procedure is presented. The first stage consists of a linear transformation of an artificially created signal that has the property of detecting step edges irrespective of the distribution of the intervals between two consecutive edges. It is demonstrated that the Hilbert transform possesses this property and also outperforms the derivative operation in the detection of step edges in the presence of noise. The second stage consists of an appropriate mapping of the filtered results into edge detection primitives. Practical confirmation of the results is given by means of examples.<>

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ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing

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