Scalar image interest point detection and description based on discrete Morse theory and geometric descriptors
The use of scalar data has arisen in many image applications which obtain data from simulated experiments, range scanners and photogrammetry. Their different nature of acquisition influences the type of processing and the analysis that may be undertaken in tasks such as registration, retrieval and recognition of structures or objects. This paper presents a new method for detecting and describing scale invariant descriptors over dense scalar data sets. The detection of interest points for each image is accomplished using an approach based on the Morse theory and descriptors are computed exploring the geometry of the data. Experiments are performed to demonstrate the effectiveness of the proposed method.