• Journal of Digital Convergence
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• v.11 no.8
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• pp.191-197
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• 2013

In this paper, we implemented a paper currency recognition system using IR(infrared) sensor. The system has 32 channel IR sensor to measure the reflection and penetration quantity of light. The IR image of paper currency of 10-bit gray scale is used to differentiate the real and counterfeit paper currency with image information from 0 to 4095. The characteristics of IR image are recognized by brightness and darkness and the positions of bright and dark portions are different between real and counterfeit paper currency. The price of IR sensors were relatively high, however, it is good price in these days due to mass production to apply to counterfeit detection area. We used a software table having the IR characteristics of real paper currency to compare with the IR images of the input paper currency. The performance of the implemented system shows 1-2% error rates for Euro real paper currency and 0% error rates for various counterfeit paper currencies of several countries.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1121-1129
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• 2022

Object recognition is carried out using RGB images in various object recognition studies. However, RGB images in dark illumination environments or environments where target objects are occluded other objects cause poor object recognition performance. On the other hand, IR images provide strong object recognition performance in these environments because it detects infrared waves rather than visible illumination. In this paper, we propose an RGB-IR fusion model, high-frequency interchange network (HINet), which improves object recognition performance by combining only the strengths of RGB-IR image pairs. HINet connected two object detection models using a mutual high-frequency transfer (MHT) to interchange advantages between RGB-IR images. MHT converts each pair of RGB-IR images into a discrete cosine transform (DCT) spectrum domain to extract high-frequency information. The extracted high-frequency information is transmitted to each other's networks and utilized to improve object recognition performance. Experimental results show the superiority of the proposed network and present performance improvement of the multispectral object recognition task.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.174-174
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• 2017

농지의 구성물을 인식하는 기술은 농작업 기계를 로봇으로 전환하는데 필요한 기술 중 하나이다. 하지만 실외에서는 태양광과 날씨 변화에 따른 광 조건의 변화가 매우 커서 기존의 영상처리 방법으로 구성물을 인지하는데 한계가 있었다. 본 연구에서는 광 조건의 변화에 따른 영향을 줄이는 방안으로 IR 이미지를 이용한 농지 구성물의 인지를 수행하였다. 농지 구성물로는 토양, 식물, 멀칭비닐, 자갈을 선정하였다. 농지의 IR 이미지에서 농지 구성물을 구별하기 위한 픽셀값을 작게 적용하면 미세한 구분은 가능하지만 토양, 식물, 멀칭 비닐 등을 구성물 단위로 구별할 대는 후처리가 필요로 해지는 문제가 발생하였다. 본 연구에서는 IR 영상의 픽셀값을 평균 처리하여 농지 구성물의 인지를 수행 때의 효과를 확인 하였다. 평균 처리하는 픽셀값이 많을수록 처리속도가 빠르고, 작은 노이즈를 제어하는 효과가 있었지만, 픽셀값이 너무 커지면 구조물의 구별 정확도가 떨어졌다. 이 결과를 바탕으로 농지 구성물 인지를 위한 효율적인 IR 이미지 평균 처리 수준을 확인하였다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.1
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• pp.31-40
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• 2024

Recently, static analysis-based signature and pattern detection technologies have limitations due to the advanced IT technologies. Moreover, It is a compatibility problem of multiple architectures and an inherent problem of signature and pattern detection. Malicious codes use obfuscation and packing techniques to hide their identity, and they also avoid existing static analysis-based signature and pattern detection techniques such as code rearrangement, register modification, and branching statement addition. In this paper, We propose an LLVM IR image-based automated static analysis of malicious code technology using machine learning to solve the problems mentioned above. Whether binary is obfuscated or packed, it's decompiled into LLVM IR, which is an intermediate representation dedicated to static analysis and optimization. "Therefore, the LLVM IR code is converted into an image before being fed to the CNN-based transfer learning algorithm ResNet50v2 supported by Keras". As a result, we present a model for image-based detection of malicious code.

• The Optical Journal
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• s.176
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• pp.44-48
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• 2020

• Journal of Digital Convergence
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• v.16 no.12
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• pp.301-307
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• 2018

The most of the IR focus on the method for searching the document, so the keyword-based IR system is not able to reflect the feature information of the image. In order to overcome these limitations, we have developed a system that can search similar images based on the vector information of images, and it can search for similar images based on sketches. The proposed system uses the GAN to up sample the sketch to the image level, convert the image to the vector through the CNN, and then retrieve the similar image using the vector space model. The model was learned using fashion image and the image retrieval system was developed. As a result, the result is showed meaningful performance.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.5
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• pp.476-486
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• 2022

Synthetic dynamic infrared image generation from the given virtual environment is being the primary goal to simulate the output of the infra-red(IR) camera installed on a vehicle to evaluate the control algorithm for various search & reconnaissance missions. Due to the difficulty to obtain actual IR data in complex environments, Artificial intelligence(AI) has been used recently in the field of image data generation. In this paper, CycleGAN technique is applied to obtain a more realistic synthetic IR image. We added the Structural Similarity Index Measure(SSIM) loss function to the L1 loss function to generate a more realistic synthetic IR image when the CycleGAN image is generated. From the simulation, it is applicable to the guided-missile flight simulation tests by using the synthetic infrared image generated by the proposed technique.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.155-166
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• 2021

Most object detection algorithms are studied based on RGB images. Because the RGB cameras are capturing images based on light, however, the object detection performance is poor when the light condition is not good, e.g., at night or foggy days. On the other hand, high-quality infrared(IR) images regardless of weather condition and light can be acquired because IR images are captured by an IR sensor that makes images with heat information. In this paper, we performed the object detection algorithm based on the compression ratio in RGB and IR images to show the detection capabilities. We selected RGB and IR images that were taken at night from the Free FLIR Thermal dataset for the ADAS(Advanced Driver Assistance Systems) research. We used the pre-trained object detection network for RGB images and a fine-tuned network that is tuned based on night RGB and IR images. Experimental results show that higher object detection performance can be acquired using IR images than using RGB images in both networks.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.4 no.4
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• pp.34-38
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• 2005

This is a widespread requirement for low cost lightweight thermal imaging sensors for both military and civilian applications. Today, a large number of uncooled infrared detector developments are under progress due to the availability of silicon technology that enables realization of low cost IR sensor. System prices are continuing to drop, and swelling production volume will soon drive process substantially lower. The feasibility of micromechanical optical and infrared (IR) detection using microcantilevers is demonstrated. Microcantilevers provide a simple Structurefor developing single- and multi-element sensors for visible and infrared radiation that are smaller, more sensitive and lower in cost than quantum or thermal detectors. Microcantilevers coated with a heat absorbing layer undergo bending due to the differential stress originating from the bimetallic effect. This paper reports a micromachined silicon uncooled thermal imager intended for applications in automated process control. This paper presents the design, fabrication, and the behavior of cantilever for thermomechanical sensing.

• The Journal of the Korea Contents Association
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• v.11 no.5
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• pp.205-215
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• 2011

Films are sensitive to ultraviolet rays and in contrast, digital camera sensors are extremely sensitive to infrared rays due to the differences in spectral characteristics. As a result, all digital cameras that use CCD or CMOS are equipped with IR Cut-Off Filter on the overall sensor. Complete block out of infrared rays is ideal, but the actual experiment results showed that infrared rays were not being blocked out completely. Infrared permeability was also different for each camera. Therefore, this study aims to analyze the effect of the minute quantities of infrared rays, which get transmitted due to mechanical properties of IR Cut-Off Filters that are installed on digital cameras, on digital picture images. The results obtained by carrying out a comparative analysis of a UV Filter (infrared transmitting state) and a UV-IR Filter (infrared blocked out state) are as follows. It was confirmed that the minute quantities of infrared rays do affect dynamic range and resolution to some extent, despite the little or no difference in noise and color reproduction.