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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science
Kwang Baek Kim
Silla University
Computer Science & IT Electrical & Electronics Engineering

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Depth image correction for intel realsense depth camera Hyun Jun Park; Kwang Baek Kim
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 2: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i2.pp1021-1027

Abstract

Intel RealSense depth camera provides depth image using infrared projector and infrared camera. Using infrared radiation makes it possible to measure the depth with high accuracy, but the shadow of infrared radiation makes depth unmeasured regions. Intel RealSense SDK provides a postprocessing algorithm to correct it. However, this algorithm is not enough to be used and needs to be improved. Therefore, we propose a method to correct the depth image using image processing techniques. The proposed method corrects the depth using the adjacent depth information. Experimental results showed that the proposed method corrects the depth image more accurately than the Intel RealSense SDK.
Colored facial image restoration by similarity enhanced implicative fuzzy association memory Kwang Baek Kim; Doo Heon Song
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 1: January 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i1.pp199-204

Abstract

Image restoration refers to the recovery of an underlying image from an observation that has been corrupted by various types of noise. In a digital forensic software, such image restoration process should be noise-tolerant, robust, fast, and scalable.  In this paper, we apply implicative fuzzy association memory structure in colored facial image restoration with enhanced similarity measure involved in output computarion. The efficacy if the proposed fuzzy associative memory model is verified by the experiment in that it was 95% successful (with zero mean square error) out of 20 tested images.
Extracting acoustic shadowing from ultrasound image using local difference Hyun Jun Park; Kwang Baek Kim
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 1: January 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i1.pp205-209

Abstract

We propose a method for extracting acoustic shadowing from ultrasound image. If we locate the acoustic shadowing exactly then we can also extract the hyperechoic substances with a high probability. The proposed method reconstitutes an original ultrasound image to simplify calculations and uses the locally horizontal difference to extract shadow candidates. The shadow candidates are classified into start and finish point, and shadow regions are extracted by using them. The experiment results show the proposed method extracts 23 of 27 acoustic shadows from ultrasonogram efficiently and it can be used in wide applications.
Co-Authors Doo Heon Song Hae-Jung Lee Hosung Nho Hyun Jun Park Hyun Jun Park Hyun Jun Park Hyun-Min Choi Jong Hee Lee Joonsung Park Kyung-Ae Kim Sang-Seok Yun Young Woon Woo