The article analyses the issues related to detection and contour approximation of road surface defects, in particular, road potholes captured by a smart device camera. The assessment of measurements, obtained after image analysis and real objects, will be disclosed with a view to depict the measurement bias. The difference from all the other methods, mentioned in the literature, is that only 2D images captured by one camera were used in this investigation with a view to identify the contour of road potholes and get its parameterised representation. In practice, according to other authors, the most common approach to obtain a parameterised description of a pothole incorporates not only cameras, but also other various sensors such as accelerometer, global positioning systems, laser, hyperspectral imagery, infrared or ultrasonic sensors. In this article, we present a method that allows recognising a pothole object in terms of its colour, shape, and structure. The method discussed was applied to real world images to detect and outline the road pothole contour. Finally, the evaluation of approximation accuracy by empirical research techniques has been accomplished.

No abstract

Image quality assessment still remains a highly relevant problem, and objective quality assessment methods are being actively developed. The methods, based on the Structural Similarity index method, have become very popular during the last decade. However, their sensitivity has been investigated using only small images and only in the cases of obvious image distortions. In this paper, we have investigated a quality assessment of high-resolution images with low distortions after compression using the Structural Similarity index method. The specific cases, related to the usage of this method for high-resolution images, are analyzed, and the problems that occur when using the method are identified. Experimental investigations have shown that image downsampling is necessary when the image quality is assessed by the Structural Similarity index method. Moreover, a sensitive algorithm suitable for the comparison of the quality of highresolution images with small distortions is proposed and investigated in the paper.