Road identification in aerial images on fractional differential and one-pass ridge edge detection

Abstract

Abstract. A method for detecting and identifying thin and vague roads in aerial images is proposed. The method first smooths an image by using a Gaussian filter, then uses a fractional differential operator to enhance the image for sharpening roads, then applies a one-pass ridge edge detection algorithm to roughly detect the roads, and finally utilizes a number of post functions to accurately identify roads. For each detected point in an aerial road image, the new ridge detection algorithm detects if it is a candidate for the ridge edge points by searching through four different directions. After that, the extracted segments of lines/curves are smoothed and their gaps are linked according to preset thresholds of lengths and directions, and the noisy lines are removed based on the rules of the curve length and shape information. If roads are thick, the image can be shrunk to a road with a width less than six pixels, then the detection result for the course resolution image is mapped into the original image to accurately re-identify the road. In experiments, by comparison to traditional methods, the studied method can have better detection results for thin and vague roads, which are difficult to detect with traditional algorithms.

Influence of Fractional Differential on Correlation Coefficient between EC1:5 and Reflectance Spectra of Saline Soil

“…After holding the First Conference on Fractional Calculus and its Applications on June 1974 [17], the fractional calculus has been widely applied in various fields [18][19][20][21][22][23][24][25][26], because the fractional models are more accurate than the integer ones. In the field of remote sensing, fractional calculus is mainly used for image enhancement and feature extraction [27][28][29][30].…”

Rock fissure pattern characterization by combining 1-D fractal dimension and statistical analysis

“…For a grey level fracture image, if the image is vague, the image enhancement can be carried out by fractional differential [9], [10] or Retinex [11] based methods. After the improved Canny edge detection [12] or one-pass ridge edge detection [13] or the detection on local gray value minima [14], the image can be binarized. In a binary image, the skeleton is used for representing the main feature of an object, which is widely used in many applications such as character identification and face recognitions, geology and medicine applications.…”