• Title/Summary/Keyword: 특징 검출

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A Study on AR Algorithm Modeling for Indoor Furniture Interior Arrangement Using CNN

  • Ko, Jeong-Beom;Kim, Joon-Yong
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.10
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    • pp.11-17
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    • 2022
  • In this paper, a model that can increase the efficiency of work in arranging interior furniture by applying augmented reality technology was studied. In the existing system to which augmented reality is currently applied, there is a problem in that information is limitedly provided depending on the size and nature of the company's product when outputting the image of furniture. To solve this problem, this paper presents an AR labeling algorithm. The AR labeling algorithm extracts feature points from the captured images and builds a database including indoor location information. A method of detecting and learning the location data of furniture in an indoor space was adopted using the CNN technique. Through the learned result, it is confirmed that the error between the indoor location and the location shown by learning can be significantly reduced. In addition, a study was conducted to allow users to easily place desired furniture through augmented reality by receiving detailed information about furniture along with accurate image extraction of furniture. As a result of the study, the accuracy and loss rate of the model were found to be 99% and 0.026, indicating the significance of this study by securing reliability. The results of this study are expected to satisfy consumers' satisfaction and purchase desires by accurately arranging desired furniture indoors through the design and implementation of AR labels.

Design of Cold-junction Compensation and Disconnection Detection Circuits of Various Thermocouples(TC) and Implementation of Multi-channel Interfaces using Them (다양한 열전쌍(TC)의 냉점보상과 단선감지 회로설계 및 이를 이용한 다채널 인터페이스 구현)

  • Hyeong-Woo Cha
    • Journal of IKEEE
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    • v.27 no.1
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    • pp.45-52
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    • 2023
  • Cold-junction correction(CJC) and disconnection detection circuit design of various thermocouples(TC) and multi-channel TC interface circuit using them were designed. The CJC and disconnection detection circuit consists of a CJC semiconductor device, an instrumentation amplifier(IA), two resistors and a diode for disconnection detection. Based on the basic circuit, a multi-channel interface circuit was also implemented. The CJC was implemented using compensation semiconductor and IA, and disconnection detection was detected by using two resistor and a diode so that IA input voltage became -0.42V. As a result of the experiment using R-type TC, the error of the designed circuit was reduced from 0.14mV to 3㎶ after CJC in the temperature range of 0℃ to 1400℃. In addition, it was confirmed that the output voltage of IA was saturated from 88mV to -14.2V when TC was disconnected from normal. The output voltage of the designed circuit was 0V to 10V in the temperature range of 0℃ to 1400℃. The results of the 4-channel interface experiment using R-type TC were almost identical to the CJC and disconnection detection results for each channel. The implemented multi-channel interface has a feature that can be applied equally to E, J, K, T, R, and S-type TCs by changing the terminals of CJC semiconductor devices and adjusting the IA gain.

Characterization of coated colorless synthetic moissanite (코팅된 무색 합성 모이사나이트의 특징)

  • Choi, Hyunmin;Kim, Youngchool;Jang, Hansoo;Seok, Jeongwon
    • Journal of the Korean Crystal Growth and Crystal Technology
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    • v.32 no.1
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    • pp.7-11
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    • 2022
  • Recently, Hanmi Gemological Institute & Laboratory (HGI) had an opportunity to examine 5 transparent synthetic moissanite. The round brilliants ranged from 0.93 to 0.96 ct and had a colorless, pink, yellow, blue, and red color. Advanced testing results, including Fourier-transform infrared (FTIR) and Raman spectroscopy, identified all the specimens as synthetic moissanite. Under the microscope, all samples except the colorless were confirmed to be a synthetic moissanite coated with a colored film. EDXRF chemical analysis detected very weak X-ray fluorescence peak characteristics of Ca, Ti, and Co in the colored samples. These features were not detected in the colorless sample. Raman spectroscopy investigation was unable to detect the 1332 cm-1 (produced by sp3 bonding of carbon atoms) or the ~1550 cm-1 (produced by graphite-related sp2 bonding) peak in the colorless sample. The SEM image of the colorless sample showed no indication of a coating. The TEM image of the colorless sample revealed the presence of a 3~8 nm thick layer on the moissanite. Moreover, from the corresponding STEM Z-contrast image combined with the energy-dispersive X-ray spectroscopy (EDX) line profiles and EDX elemental maps, this layer was estimated to be carbon, silicon and oxygen.

Plasma Amino Acid and Urine Organic Acid in Diagnosis of MELAS (멜라스 증후군 진단에서의 혈장 아미노산과 소변 유기산 분석)

  • Ji-Hoon Na;Young-Mock Lee
    • Journal of The Korean Society of Inherited Metabolic disease
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    • v.23 no.1
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    • pp.17-24
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    • 2023
  • Purpose: In the past, detection of metabolic abnormalities in plasma amino acid (PAA) and urine organic acid (UOA) has been widely used to diagnose clinical mitochondrial diseases, such as mitochondrial encephalomyopathy with lactic acidosis and stroke-like episodes (MELAS). In this study, the diagnostic values of PAA and UOA were reviewed, and their effectiveness in the diagnosis of MELAS was examined retrospectively. Methods: Blood and urine samples at the time of diagnosis were collected from all clinically diagnosed MELAS patients (n=31), and PAA and UOA tests were performed. All samples were collected in a fasting state to minimize artifacts in the results. The difference in the ratio of abnormal metabolites of PAA and UOA at initial diagnosis was statistically compared between the MELAS with genetic confirmation (n=19, m.3243A>G mutation) and MELAS without genetic confirmation (n=12) groups. The MELAS without genetic confirmation group was used as control. Results: Comparison of PAA and UOA between the two groups revealed that no abnormal metabolites showed characteristic differences between gene-confirmed MELAS patients with and those without genetic confirmation. Conclusions: Abnormal values of metabolites in PAA or UOA might be useful as a screening test but are not sufficient to diagnose MELAS patients.

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Elucidation of new anti-impotency analogue in food (식품 중 발기부전치료제 유사물질 규명)

  • Suh, Junghyuck;Choi, Jangduck;Park, Kunsang;Hu, Soojung;Yoon, Taehyung;Kim, Eunju;Han, Seungwoo;Kim, Sohee;Lee, Kwangho;Kwan, Sungwon;Kim, Deukjoon
    • Analytical Science and Technology
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    • v.22 no.4
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    • pp.345-353
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    • 2009
  • The new anti-impotency analogue was identified in food source. Detection of this analogue was accomplished through screening of food samples by liquid chromatography/photodiode array detector. The spectrum pattern of analogue compound was similar to that observed for hongdenafil which was analogue of sildenafil. This new compound was isolated and purified using the liquid-liquid extraction, thin layer chromatography, column chromatography and preparative HPLC. And then those structure were identified using analytical instruments such as HPLC/PDA, LC/MS/MS and NMR. The compound was given a name to oxohongdenafil which was replaced with acetyl oxoethylpiperazinyl residue instead of sulfonyl piperazine group of sildenafil. The regulation for the abovementioned analogue, oxohongdenafil, was established by Standard of Korean food code.

The Study of Digitalization of Analog Gauge using Image Processing (이미지 처리를 이용한 아날로그 게이지 디지털화에 관한 연구)

  • Seon-Deok Kim;Cherl-O Bae;Kyung-Min Park;Jae-Hoon Jee
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.4
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    • pp.389-394
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    • 2023
  • In recent years, use of machine automation is rising in the industry. Ships also obtain machine condition information from sensor as digital information. However, on ships, crew members regularly surveil the engine room to check the condition of equipment and their information through analog gauges. This is a time-consuming and tedious process and poses safety risks to the crew while on surveillance. To address this, engine room surveillance using an autonomous mobile robot is being actively explored as a solution because it can reduce time, costs, and the safety risks for crew. Analog gauge reading using an autonomous mobile robot requires digitization for the robot to recognize the gauge value. In this study, image processing techniques were applied to achieve this. Analog gauge images were subjected to image preprocessing to remove noise and highlight their features. The center point, indicator point, minimum value and maximum value of the analog gauge were detected through image processing. Through the straight line connecting these points, the angle from the minimum value to the maximum value and the angle from the minimum value to indicator point were obtained. The obtained angle is digitized as the value currently indicated by the analog gauge through a formula. It was confirmed from the experiments that the digitization of the analog gauge using image processing was successful, indicating the equivalent current value shown by the gauge. When applied to surveillance robots, this algorithm can minimize safety risks and time and opportunity costs of crew members for engine room surveillance.

Reproducing Summarized Video Contents based on Camera Framing and Focus

  • Hyung Lee;E-Jung Choi
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.10
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    • pp.85-92
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    • 2023
  • In this paper, we propose a method for automatically generating story-based abbreviated summaries from long-form dramas and movies. From the shooting stage, the basic premise was to compose a frame with illusion of depth considering the golden division as well as focus on the object of interest to focus the viewer's attention in terms of content delivery. To consider how to extract the appropriate frames for this purpose, we utilized elemental techniques that have been utilized in previous work on scene and shot detection, as well as work on identifying focus-related blur. After converting the videos shared on YouTube to frame-by-frame, we divided them into a entire frame and three partial regions for feature extraction, and calculated the results of applying Laplacian operator and FFT to each region to choose the FFT with relative consistency and robustness. By comparing the calculated values for the entire frame with the calculated values for the three regions, the target frames were selected based on the condition that relatively sharp regions could be identified. Based on the selected results, the final frames were extracted by combining the results of an offline change point detection method to ensure the continuity of the frames within the shot, and an edit decision list was constructed to produce an abbreviated summary of 62.77% of the footage with F1-Score of 75.9%

CNN-LSTM-based Upper Extremity Rehabilitation Exercise Real-time Monitoring System (CNN-LSTM 기반의 상지 재활운동 실시간 모니터링 시스템)

  • Jae-Jung Kim;Jung-Hyun Kim;Sol Lee;Ji-Yun Seo;Do-Un Jeong
    • Journal of the Institute of Convergence Signal Processing
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    • v.24 no.3
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    • pp.134-139
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    • 2023
  • Rehabilitators perform outpatient treatment and daily rehabilitation exercises to recover physical function with the aim of quickly returning to society after surgical treatment. Unlike performing exercises in a hospital with the help of a professional therapist, there are many difficulties in performing rehabilitation exercises by the patient on a daily basis. In this paper, we propose a CNN-LSTM-based upper limb rehabilitation real-time monitoring system so that patients can perform rehabilitation efficiently and with correct posture on a daily basis. The proposed system measures biological signals through shoulder-mounted hardware equipped with EMG and IMU, performs preprocessing and normalization for learning, and uses them as a learning dataset. The implemented model consists of three polling layers of three synthetic stacks for feature detection and two LSTM layers for classification, and we were able to confirm a learning result of 97.44% on the validation data. After that, we conducted a comparative evaluation with the Teachable machine, and as a result of the comparative evaluation, we confirmed that the model was implemented at 93.6% and the Teachable machine at 94.4%, and both models showed similar classification performance.

Recent Progress in Colorimetric Assays Using the Absorption of Plasmonic Gold Nanoparticles (플라즈모닉 금 나노입자의 흡광 특성을 활용한 생화학적 비색 분석법 연구 동향)

  • Bong-Geun Kim;Sang Bin Yoon;Sukyeong Hwang;Hyon Bin Na
    • Applied Chemistry for Engineering
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    • v.35 no.2
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    • pp.67-78
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    • 2024
  • Light absorption has potential as a signal in biochemical analyses due to its simplicity in measurement and interpretational clarity. Among substances that generate absorption signals, gold nanoparticles possess advantages such as chemical stability, biological compatibility, and unique optical properties from the localized surface plasmon resonance (LSPR) in the visible light range. They also exhibit versatility compared to other colorimetric substances effective only for specific target molecules, as they easily conjugate with various detection active substances like antibodies and aptamers. Particularly due to advantages such as low cost, ease of particle synthesis, and high environmental stability compared to enzyme-based colorimetric methods, gold nanoparticles are extensively researched as signal substances in colorimetric assays. This review summarizes various strategies utilizing gold nanoparticles as absorption signal substances, focusing on recent research. Based on the characteristics of gold nanoparticles, where the optical property is influenced by particle morphology, literature is classified and reviewed based on strategies controlling the shape of gold nanoparticles during signal generation. Through this, it is observed that gold nanoparticles, which have been used as absorption signal substances, continue to be actively researched, affirming their potential for broad and continuous improvement in the future.

Multi-View 3D Human Pose Estimation Based on Transformer (트랜스포머 기반의 다중 시점 3차원 인체자세추정)

  • Seoung Wook Choi;Jin Young Lee;Gye Young Kim
    • Smart Media Journal
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    • v.12 no.11
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    • pp.48-56
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    • 2023
  • The technology of Three-dimensional human posture estimation is used in sports, motion recognition, and special effects of video media. Among various methods for this, multi-view 3D human pose estimation is essential for precise estimation even in complex real-world environments. But Existing models for multi-view 3D human posture estimation have the disadvantage of high order of time complexity as they use 3D feature maps. This paper proposes a method to extend an existing monocular viewpoint multi-frame model based on Transformer with lower time complexity to 3D human posture estimation for multi-viewpoints. To expand to multi-viewpoints our proposed method first generates an 8-dimensional joint coordinate that connects 2-dimensional joint coordinates for 17 joints at 4-vieiwpoints acquired using the 2-dimensional human posture detector, CPN(Cascaded Pyramid Network). This paper then converts them into 17×32 data with patch embedding, and enters the data into a transformer model, finally. Consequently, the MLP(Multi-Layer Perceptron) block that outputs the 3D-human posture simultaneously updates the 3D human posture estimation for 4-viewpoints at every iteration. Compared to Zheng[5]'s method the number of model parameters of the proposed method was 48.9%, MPJPE(Mean Per Joint Position Error) was reduced by 20.6 mm (43.8%) and the average learning time per epoch was more than 20 times faster.

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