Mohammed Eltahir's blog

  Abstract: Edge detection is an essential pre-processing procedure involved in most digital photogrammetry applications. Edge detection captures the object's physical boundaries, a crucial property of objects in the image. The amount of information provided by the edge detection operator is a crucial factor for the extraction of Corner points. Each edge map has a unique amount of information that differs depending on the used edge detection operator. Edge detection operators get optimized to solve a tremendous number of issues such as noise, edge structure, edge orientation, and computation time. Because of these issues and others, there is no single operator that fits all kinds of applications and purposes. So, it is a critical task to measure the impact of each edge detection operator on the extraction of corner points and choose the operator that yields a precise localization of corner points. This study evaluates the impact of the edge detection operator and measures its eff...

Abstract: Low-level feature extraction such as lines and points (i.e. corners), forms a fundamental step in digital photogrammetry and other fields. They supply the inputs for the photogrammetric orientation procedures; and they serve as an intermediate inputs for other processes such object recognition. With the accumulation of knowledge, the research community is in a better position to develop new generations of smart algorithms and solutions that possess a new level of maturity and understanding for the underlying challenges of automation. To this end, this paper presents an innovative approach for corner point extraction that combines the outputs from classical point feature operators with Hough Transform to generate a better hypothesis for a corner point that can be used for applications in urban areas. In particular, extracted point features were used to guide line extraction in a local neighbourhood by Hough Transform. Then the corner points that will be obtained from lines i...