KakaoBank has been granted a patent for a hologram detection method using neural network models. The method involves capturing images with varying flash intensities to detect holograms in different regions of an object. By comparing detection results, the authenticity of the object can be determined. GlobalData’s report on KakaoBank gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on KakaoBank, Virtual banking assistant was a key innovation area identified from patents. KakaoBank's grant share as of February 2024 was 30%. Grant share is based on the ratio of number of grants to total number of patents.
Hologram detection method using neural network model
A recently granted patent (Publication Number: US11907783B2) discloses a hologram detection method that involves setting multiple detection unit regions within a detection object, capturing images in both flash off and flash on states, inputting these images into a neural network model to determine the presence of a hologram, and comparing the results to authenticate the object. The neural network model is trained using various learning images with labeled hologram presence information in different regions. The method also includes adjusting flash intensity step-by-step and re-capturing images if the hologram is not detected or the detection regions differ between images.
Furthermore, the patent also covers a hologram detection service providing server that implements the aforementioned method. This server includes components such as a detection unit region setting unit, an image receiver, a hologram detector utilizing a neural network model, and an authenticity determiner. The server is capable of determining the authenticity of an object based on the comparison of detection regions in images captured with varying flash intensities. Additionally, the server can adjust flash intensity incrementally and re-capture images if necessary to ensure accurate hologram detection. The neural network model used by the server is trained using labeled learning images containing hologram presence information in different regions, enhancing the accuracy of the detection process.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
