Automatic Georeferencing of Topographic Map Sheets Using OpenCV and Tesseract

The authors developed a pipeline for the automatic georeferencing of older 1 : 25 000 topographic map sheets of Hungary. The first step is the detection of the corners of the map content, then the recognition of the sheet identifier. These maps depict geographic quadrangles whose extent can be derived from the sheet ID. The sheet corners are used as GCPs for the georeference.The whole process is implemented in Python, using various open source libraries: OpenCV for image processing, Tesseract for OCR and GDAL for georeferencing.1147 map sheets were processed with an average speed of 4 seconds per sheet. False detection of the corners is automatically filtered by geometric analysis of the detected GCPs, while the sheet IDs are validated using regular expressions. The error of corner detection is under 1% of the sheet size for 89% of the sheets, under 2% for 99%. The sheet ID recognition success rate is 75.9%.Although the system is finetuned to a specific map series, it can be easily adapted to any other map series having approximately rectangular frame.

A Corner Detection Algorithm Based on Regional Center of Mass in Imaging through Water Surface

Structural light active imaging can obtain more information about the target scene, which is widely used in image registration,3D reconstruction of objects and motion detection. Due to the random fluctuation of water surface and complex underwater environment, the current corner detection algorithm has the problems of false detection and uncertainty. This paper proposes a corner detection algorithm based on the region centroid extraction. Experimental results show that, compared with the traditional detection algorithms, the proposed algorithm can extract the feature point information of the image in real time, which is of great significance to the subsequent image restoration.

Integrity and Multimedia Data Management using Emerging Technologies in the Healthcare Applications-Part II

In the present era of research and technology, several emerging concepts, like Wireless Sensor Networks (WSN), Body Wireless Sensor Networks (BWSN), Internet of Things (IoT), Cloud, Fog, Edge, SDN, and Big Data Analytics, can support IoT for design and development of intelligent systems in diverse domains. This special issue aims to concentrate on all aspects and future research directions related to this specific area of multimedia-based emerging technologies. We received 22 manuscripts in total for this special issue across the globe, and after the rigorous review process, only 5 manuscripts have been accepted for publication. The commitments for this Special Issue are reviewed as follows: Feng Zhao and Gaurav Dhiman contribute an article titled “Analysis of Data Point Cloud Preprocessing and Feature Angle Detection Algorithm” In this paper, the theory of computer vision and reverse engineering has been used to obtain the data of the segmented hull with the method of digitizing the physical parts. The simulation results show that the efficiency of the edge extraction algorithm based on mathematical morphology is 30%, which is found to be higher than the mesh generation method. An adaptive corner detection algorithm based on the edge can adaptively determine the size of the support area and accurately detect the corner position [1].......

3D-modeling of Augmented Reality objects using Shi-Tomasi corner detection algorithms

This article covers development of the Python-based software module for Blender 3D, as well as it covers research of Shi-Tomasi corner detection algorithm using the developer’s construction documents. The corners detected may be used for further three - dimensional modelling, replanting not requiring adjustment of the construction documents, or may be used for retrieval of the accurate data.