Enhance Photo Document for software Integration

Abstract

Data integration is a critical component of Software Engineering (SWE) since it guarantees that various software systems, applications, and datasets work together seamlessly. This connection allows for the aggregation of data from different sources, improving data consistency and precision. This paper presents a comprehensive methodology for auto-enhancing document images of University of Mosul data centers and their quality assessment through data integration with a cloud platform. Our approach has two stages: integration and cloud platform. The university's data center is seamlessly connected to a cloud platform using a FastAPI during integration, allowing efficient data exchange while maintaining data protection. The cloud platform stage receives picture document representations and enhances them with tools and algorithms developed for image enhancement. The approaches employed in this study encompass image scaling, similarity evaluation utilising the Histogram of Oriented Gradients (HOG) algorithm, image warping employing the FLANN (Fast Library for Approximate Nearest Neighbours) algorithm, and image quality enhancement by the application of a Laplacian sharpening filter. Furthermore, the study includes many evaluations of feature extraction techniques, document enhancement algorithms, image similarity algorithms, and their practical implementation outcomes in cloud systems.. The proposed integrated cloud-based document enhancement has shown exceptional efficiency in data sharing and precise analysis and enhancement of picture documents within the university's data center.