Lin, Wenguang, Yan, Wenchao, Chen, Zhizhen ORCID: https://orcid.org/0000-0001-6656-5854 and Xiao, Renbin (2023) Research on product appearance patent spatial shape recognition for multi-image feature fusion. Multimedia Tools and Applications. ISSN 1380-7501 (Print), 1573-7721 (Online) (doi:10.1007/s11042-023-16477-5)

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Abstract

In the process of patent retrieval, the traditional content-based single image retrieval method mainly has the following two reasons: a) semantic deviation caused by text description, b) the similarity of a single pixel in the image is high but the whole is inconsistent. Low accuracy leads to unsatisfactory retrieval results, which makes it difficult to obtain product design information timely and effectively and reduces design efficiency. How to obtain data quickly and accurately has become a challenging problem. In this paper, by analyzing the problems existing in Locarno classification method, combined with the characteristics of the patent image, a new improved method is proposed. Firstly, the structural features of product parts are extracted through segmentation. Subsequently, combine it with multi-view image fusion to determine the spatial shape of product parts jointly. Finally, the spatial shape of key structures is confirmed to refine the specific search range as well as improve the search accuracy. The feasibility and effectiveness of the proposed method are verified by taking a shower appearance patent as an example.

Item Type:	Article
Uncontrolled Keywords:	image segmentation; support vector machines; multi-image fusion; patent image
Subjects:	H Social Sciences > HF Commerce N Fine Arts > N Visual arts (General) For photography, see TR N Fine Arts > NC Drawing Design Illustration
Faculty / School / Research Centre / Research Group:	Faculty of Business Greenwich Business School > Political Economy, Governance, Finance and Accountability (PEGFA)
Last Modified:	02 Dec 2024 16:09
URI:	http://gala.gre.ac.uk/id/eprint/43753

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