Title: Using the BIRCH algorithm and affinity propagation, an advanced descriptor for video processing

Authors: Jayanta Mondal; Jitendra Pramanik; Satyajit Pattnaik; Bijay Kumar Paikaray

Addresses: School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, 751024, India ' Akiko Sherman Infotech Pvt. Ltd. Deputed at the Client Location, Department of Agriculture & Farmers Welfare, National Informatics Centre, Odisha State Centre, Odisha, 751001, India ' Faculty of Engineering and Technology, Sri Sri University, Cuttack, Odisha, 754006, India ' Department of Computer Science and Engineering, Siksha 'O' Anusandhan (Deemed to be) University, Bhubaneswar, Odisha, 751030, India

Abstract: Video summarisation provides concise and non-redundant information for object and intrusion detection in video surveillance. As video content continues to expand quickly, an automatic video summary would be helpful for anyone who wants to learn more quickly and with less effort. Most existing methods depend on various network architectures to train a single score predictor for shot rating and selection. This study addresses the issue of video summarisation, which involves selecting significant frames to succinctly and comprehensively express the original film's material. The current paper presents a comparative study of the application of advanced texture descriptors local phase quantisation (LPQ), local ternary pattern (LTP), and local binary pattern (LBP) in the process of video summarisation. Clusters of keyframes have been extracted by unsupervised learning algorithms - Affinity Propagation & BIRCH. The performance of the proposed video summarising method has shown good trial results.

Keywords: LTP; local ternary pattern; LBP; local binary pattern; affinity propagation; LPQ; local phase quantisation; BIRCH; key feature.

DOI: 10.1504/IJDATS.2026.151636

International Journal of Data Analysis Techniques and Strategies, 2026 Vol.18 No.1, pp.25 - 40

Received: 26 Sep 2022
Accepted: 03 Feb 2024
Published online: 11 Feb 2026 *

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