Feature Extraction by Rank-Order Filtering for Image Segmentation

The aim of this paper is to outline a unified approach to feature extraction for segmentation purposes by means of the rank-order filtering of grey values in a neighbourhood of each pixel of a digitized image. In the first section an overview of rank-order filtering for image processing is given, and a fast histogram algorithm is proposed. Section 2 deals with the extraction of a “locally most representative grey value”, defined as the maximum of the local histogram density function. In Section 3 several textural features are described, which can be extracted from the local histogram by means of rank-order filtering, and their properties are discussed. Section 4 formulates some general requirements to be met by the process of image segmentation, and describes a method based upon the features introduced in the former sections. In the last section some experimental results applied to aerial views obtained with the segmentation method of Sect. 4 are reported. These test images have been analyzed within the scope of an investigation centered on terrain recognition for agricultural and ecological purposes.