• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.1
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• pp.23-31
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• 2009

Recently, biometric techniques such as face recognition, finger-print recognition and iris recognition have been widely applied for various applications including door access control, finance security and electric passport. This paper presents the method of using finger-vein pattern for the personal identification. In general, when the finger-vein image is acquired from the camera, various conditions such as the penetrating amount of the infrared light and the camera noise make the segmentation of the vein from the background difficult. This in turn affects the system performance of personal identification. To solve this problem, we propose the novel and fast method for extracting the finger-vein region. The proposed method has two advantages compared to the previous methods. One is that we adopt a locally adaptive thresholding method for the binarization of acquired finger-vein image. Another advantage is that the simple morphological opening and closing are used to remove the segmentation noise to finally obtain the finger-vein region from the skeletonization. Experimental results showed that our proposed method could quickly and exactly extract the finger-vein region without using various kinds of time-consuming filters for preprocessing.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.57-65
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• 2018

Conventional RF signal-based indoor localization techniques such as BLE or Wi-Fi based fingerprinting method show considerable localization errors even in small-scale indoor environments due to unstable received signal strength(RSS) of RF signals. Therefore, it is difficult to apply the existing RF-based fingerprinting techniques to large-scale indoor environments such as airports and department stores. In this paper, instead of RF signal we use the geomagnetic sensor signal for indoor localization, whose signal strength is more stable than RF RSS. Although similar geomagnetic field values exist in indoor space, an object movement would experience a unique sequence of the geomagnetic field signals as the movement continues. We use a deep neural network model called the recurrent neural network (RNN), which is effective in recognizing time-varying sequences of sensor data, to track the user's location and movement path. To evaluate the performance of the proposed geomagnetic field based indoor positioning system (IPS), we constructed a magnetic field map for a campus testbed of about $94m{\times}26$ dimension and trained RNN using various potential movement paths and their location data extracted from the magnetic field map. By adjusting various hyperparameters, we could achieve an average localization error of 1.20 meters in the testbed.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.135-155
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• 2022

This study analyzes patent trends by deriving sub-technical fields of Organic Light-Emitting Diodes (OLEDs) industry, and analyzing technology value, originality, and diversity for each sub-technical field. To collect patent data, a set of international patent classification(IPC) codes related to OLED technology was defined, and OLED-related patents applied from 2005 to 2017 were collected using a set of IPC codes. Then, a large number of collected patent documents were classified into 12 major technologies using the Latent Dirichlet Allocation(LDA) topic model and trends for each technology were investigated. Patents related to touch sensor, module, image processing, and circuit driving showed an increasing trend, but virtual reality and user interface recently decreased, and thin film transistor, fingerprint recognition, and optical film showed a continuous trend. To compare the technological value, the number of forward citations, originality, and diversity of patents included in each technology group were investigated. From the results, image processing, user interface(UI) and user experience(UX), module, and adhesive technology with high number of forward citations, originality and diversity showed relatively high technological value. The results provide useful information in the process of establishing a company's technology strategy.