Implementation of Software for Searching Similar Illustrations in Scientific Publications

This work introduces an innovative software application that is tailored to search for similar illustrations in scientific publications, addressing a key need in academic research for efficient image comparison and retrieval. The software uses advanced image processing techniques and content-based image retrieval systems, focussing on extracting and comparing distinctive features such as colour, texture, and shape in scientific illustrations. A theoretical foundation is established, outlining the complexities in image processing and retrieval relevant to academic illustration. The development phase is explored, with an emphasis on algorithm selection and methodology adaptation for accurate feature extraction and image comparison. The efficacy of the application is demonstrated through extensive testing on diverse image sets from scientific papers, showcasing its ability to identify identical and near-identical illustrations accurately. The user interface is designed for accessibility, catering to users from various technical backgrounds, making this advanced image retrieval technology readily available to the academic community. The results from practical application tests confirm the high accuracy of the software in image matching, emphasising the effectiveness of the employed techniques. Conclusively, this work marks a significant contribution to the field of image processing in academic research, offering an essential tool for researchers and academicians. Highlights the importance of precise image feature extraction and comparison in building effective image retrieval systems for the scientific literature. The successful implementation and testing of the software underline its potential as an indispensable resource in academic research and information retrieval, promising to streamline the process of finding relevant illustrations in scientific publications.