Hsiao F.-TLin Y.-HYI-CHANG LU2023-06-092023-06-092021https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125229365&doi=10.1109%2fVCIP53242.2021.9675328&partnerID=40&md5=dc99ef4d87f1943259551c484d433b18https://scholars.lib.ntu.edu.tw/handle/123456789/632090In this paper, we propose a novel algorithm for summarization-based image resizing. In the past, a process of detecting precise locations of repeating patterns is required before the pattern removal step in resizing. However, it is difficult to find repeating patterns which are illuminated under different lighting conditions and viewed from different perspectives. To solve the problem, we first identify the regularity unit of repeating patterns by statistics. Then we can use the regularity unit for shift-map optimization to obtain a better resized image. The experimental results show that our method is competitive with other well-known methods. © 2021 IEEE.Image resizing; Image summarization; Repeating pattern removalComputer vision; Image resizing; Image summarization; Lighting conditions; Map optimizations; Novel algorithm; Precise locations; Repeating pattern removal; Repeating patterns; Shift maps; Computersconference paper10.1109/VCIP53242.2021.96753282-s2.0-85125229365