A Study on the Efficient Product Search Service for the Damaged Image Information
This addresses a specific issue for e-commerce users and platforms by improving search accuracy for damaged images, though it appears incremental as it applies existing image processing techniques to this domain.
The study tackled the problem of product search engines failing to recognize damaged product images by developing an image restoration system using pre-processing and inpainting algorithms, resulting in a more accurate image search system that helps users purchase desired items.
With the development of Information and Communication Technologies and the dissemination of smartphones, especially now that image search is possible through the internet, e-commerce markets are more activating purchasing services for a wide variety of products. However, it often happens that the image of the desired product is impaired and that the search engine does not recognize it properly. The idea of this study is to help search for products through image restoration using an image pre-processing and image inpainting algorithm for damaged images. It helps users easily purchase the items they want by providing a more accurate image search system. Besides, the system has the advantage of efficiently showing information by category, so that enables efficient sales of registered information.