• Title/Summary/Keyword: Optical image

Search Result 2,715, Processing Time 0.038 seconds

Identification of Multiple Cancer Cell Lines from Microscopic Images via Deep Learning (심층 학습을 통한 암세포 광학영상 식별기법)

  • Park, Jinhyung;Choe, Se-woon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2021.05a
    • /
    • pp.374-376
    • /
    • 2021
  • For the diagnosis of cancer-related diseases in clinical practice, pathological examination using biopsy is essential after basic diagnosis using imaging equipment. In order to proceed with such a biopsy, the assistance of an oncologist, clinical pathologist, etc. with specialized knowledge and the minimum required time are essential for confirmation. In recent years, research related to the establishment of a system capable of automatic classification of cancer cells using artificial intelligence is being actively conducted. However, previous studies show limitations in the type and accuracy of cells based on a limited algorithm. In this study, we propose a method to identify a total of 4 cancer cells through a convolutional neural network, a kind of deep learning. The optical images obtained through cell culture were learned through EfficientNet after performing pre-processing such as identification of the location of cells and image segmentation using OpenCV. The model used various hyper parameters based on EfficientNet, and trained InceptionV3 to compare and analyze the performance. As a result, cells were classified with a high accuracy of 96.8%, and this analysis method is expected to be helpful in confirming cancer.

  • PDF

Observation and Analysis of Green Algae Phenomenon in Soyang-ho in 2023 Using Satellite Images (위성영상을 활용한 2023년 소양호 녹조 현상 관측 및 분석)

  • Sungjae Park;Seulki Lee;Suci Ramayanti;Eunseok Park;Chang-Wook Lee
    • Korean Journal of Remote Sensing
    • /
    • v.39 no.5_1
    • /
    • pp.683-693
    • /
    • 2023
  • In this study, we used satellite images to analyze the green algae phenomenon that first occurred in Soyang-ho, which was completed in 1973. The research data used 13 optical images over a period of about 2 months from July 2023, and the area of green algae that occurred in Soyang-ho was calculated. To calculate the exact area where green algae occurred, image classification was performed based on the support vector machine algorithm. As a result, green algae in Soyang-ho occurred around the point where the impurities that caused the green algae were introduced. It seemed to temporarily decrease due to the effects of Typhoon Khanun in August 2023, but green algae increased again due to the continued heat. Soyang-ho is one of the major water sources in the metropolitan area, suggesting that we must prepare for repeated green algae outbreaks.

Analysis of the Influence of Atmospheric Turbulence on the Ground Calibration of a Star Sensor

  • Xian Ren;Lingyun Wang;Guangxi Li;Bo Cui
    • Current Optics and Photonics
    • /
    • v.8 no.1
    • /
    • pp.38-44
    • /
    • 2024
  • Under the influence of atmospheric turbulence, a star's point image will shake back and forth erratically, and after exposure the originally small star point will spread into a huge spot, which will affect the ground calibration of the star sensor. To analyze the impact of atmospheric turbulence on the positioning accuracy of the star's center of mass, this paper simulates the atmospheric turbulence phase screen using a method based on a sparse spectrum. It is added to the static-star-simulation device to study the transmission characteristics of atmospheric turbulence in star-point simulation, and to analyze the changes in star points under different atmospheric refractive-index structural constants. The simulation results show that the structure function of the atmospheric turbulence phase screen simulated by the sparse spectral method has an average error of 6.8% compared to the theoretical value, while the classical Fourier-transform method can have an error of up to 23% at low frequencies. By including a simulation in which the phase screen would cause errors in the center-of-mass position of the star point, 100 consecutive images are selected and the average drift variance is obtained for each turbulence scenario; The stronger the turbulence, the larger the drift variance. This study can provide a basis for subsequent improvement of the ground-calibration accuracy of a star sensitizer, and for analyzing and evaluating the effect of atmospheric turbulence on the beam.

Assessment of Antarctic Ice Tongue Areas Using Sentinel-1 SAR on Google Earth Engine (Google Earth Engine의 Sentienl-1 SAR를 활용한 남극 빙설 면적 변화 모니터링)

  • Na-Mi Lee;Seung Hee Kim;Hyun-Cheol Kim
    • Korean Journal of Remote Sensing
    • /
    • v.40 no.3
    • /
    • pp.285-293
    • /
    • 2024
  • This study explores the use of Sentinel-1 Synthetic Aperture Radar (SAR), processed through Google Earth Engine (GEE), to monitor changes in the areas of Antarctic ice shelves. Focusing on the Campbell Glacier Tongue (CGT) and Drygalski Ice Tongue (DIT),the research utilizes GEE's cloud computing capabilities to handle and analyze large datasets. The study employs Otsu's method for image binarization to distinguish ice shelves from the ocean and mitigates detection errors by averaging monthly images and extracting main regions. Results indicate that the CGT area decreased by approximately 26% from January 2016 to January 2024, primarily due to calving events,while DIT showed a slight increase overall,with notable reduction in recent years. Validation against Sentinel-2 optical images demonstrates high accuracy,underscoring the effectiveness of SAR and GEE for continuous, long-term monitoring of Antarctic ice shelves.

Yield monitoring systems for non-grain crops: A review

  • Md Sazzadul Kabir;Md Ashrafuzzaman Gulandaz;Mohammod Ali;Md Nasim Reza;Md Shaha Nur Kabir;Sun-Ok Chung;Kwangmin Han
    • Korean Journal of Agricultural Science
    • /
    • v.51 no.1
    • /
    • pp.63-77
    • /
    • 2024
  • Yield monitoring systems have become integral to precision agriculture, providing insights into the spatial variability of crop yield and playing an important role in modern harvesting technology. This paper aims to review current research trends in yield monitoring systems, specifically designed for non-grain crops, including cabbages, radishes, potatoes, and tomatoes. A systematic literature survey was conducted to evaluate the performance of various monitoring methods for non-grain crop yields. This study also assesses both mass- and volume-based yield monitoring systems to provide precise evaluations of agricultural productivity. Integrating load cell technology enables precise mass flow rate measurements and cumulative weighing, offering an accurate representation of crop yields, and the incorporation of image-based analysis enhances the overall system accuracy by facilitating volumetric flow rate calculations and refined volume estimations. Mass flow methods, including weighing, force impact, and radiometric approaches, have demonstrated impressive results, with some measurement error levels below 5%. Volume flow methods, including paddle wheel and optical methodologies, yielded error levels below 3%. Signal processing and correction measures also play a crucial role in achieving accurate yield estimations. Moreover, the selection of sensing approach, sensor layout, and mounting significantly influence the performance of monitoring systems for specific crops.

Utility of intraoral scanner imaging for dental plaque detection

  • Chihiro Yoshiga;Kazuya Doi;Hiroshi Oue;Reiko Kobatake;Maiko Kawagoe;Hanako Umehara;Kazuhiro Tsuga
    • Imaging Science in Dentistry
    • /
    • v.54 no.1
    • /
    • pp.43-48
    • /
    • 2024
  • Purpose: Oral hygiene, maintained through plaque control, helps prevent periodontal disease and dental caries. This study was conducted to examine the accuracy of plaque detection with an intraoral scanner(IOS) compared to images captured with an optical camera. Materials and Methods: To examine the effect of color tone, artificial tooth resin samples were stained red, blue, and green, after which images were acquired with a digital single-lens reflex (DSLR) camera and an IOS device. Stained surface ratios were then determined and compared. Additionally, the deviation rate of the IOS relative to the DSLR camera was computed for each color. In the clinical study, following plaque staining with red disclosing solution, the staining was captured by the DSLR and IOS devices, and the stained area on each image was measured. Results: The stained surface ratios did not differ significantly between DSLR and IOS images for any color group. Additionally, the deviation rate did not vary significantly across colors. In the clinical test, the stained plaque appeared slightly lighter in color, and the delineation of the stained areas less distinct, on the IOS compared to the DSLR images. However, the stained surface ratio was significantly higher in the IOS than in the DSLR group. Conclusion: When employing IOS with dental plaque staining, the impact of color was minimal, suggesting that the traditional red stain remains suitable for plaque detection. IOS images appeared relatively blurred and enlarged relative to the true state of the teeth, due to inferior sharpness compared to camera images.

A Study on Design and Analysis of Method for MR-based 3D Biological Object Recognition and Matching (MR 기반 3차원 생체 객체 인식 및 정합을 위한 방법 설계와 해석 연구)

  • Jin-Pyo Jo;Yong-Bae Jeong
    • Journal of Platform Technology
    • /
    • v.12 no.2
    • /
    • pp.23-33
    • /
    • 2024
  • The development of mixed reality (MR) technology has a great influence on the research and development of medical support equipment. In particular, it supports to respond effectively to emergencies occurring in the field. MR technology enables access to first aid and field support by combining virtual information with the real world so that users can see virtual objects in the real world. However, due to the nature of the equipment, there is a limitation in accurately matching virtual objects based on user vision. To improve these limitations, this paper proposes a 3D biometric object recognition and matching algorithm in the MR environment. As a result of the experiment, when a virtual object is rendered and visualized while equipped with an optical-based HMD from the user's side, it was possible to reduce the user's field of view error and eliminate the joint-loss phenomenon during skeleton recognition. The proposed method can reduce errors between the real user's field of view and the virtual image and provide a basis for reducing errors that occur in the process of virtual object recognition and matching. It is expected that this study will contribute to improving the accuracy of the telemedicine support system for first aid.

  • PDF

Quantitative analysis of retained austenite in Nb added Fe-based alloy

  • Kwang Kyu Ko;Jin Ho Jang;Saurabh Tiwari;Hyo Ju Bae;Hyo Kyung Sung;Jung Gi Kim;Jae Bok Seol
    • Applied Microscopy
    • /
    • v.52
    • /
    • pp.5.1-5.10
    • /
    • 2022
  • The use of Pipelines for long-distance transportation of crude oil, natural gas and similar applications is increasing and has pivotal importance in recent times. High specific strength plays a crucial role in improving transport efficiency through increased pressure and improved laying efficiency through reduced diameter and weight of line pipes. TRIP-based high-strength and high-ductility alloys comprise a mixture of ferrite, bainite, and retained austenite that provide excellent mechanical properties such as dimensional stability, fatigue strength, and impact toughness. This study performs microstructure analysis using both Nital etching and LePera etching methods. At the time of Nital etching, it is difficult to distinctly observe second phase. However, using LePera etching conditions it is possible to distinctly measure the M/A phase and ferrite matrix. The fraction measurement was done using OM and SEM images which give similar results for the average volume fraction of the phases. Although it is possible to distinguish the M/A phase from the SEM image of the sample subjected to LePera etching. However, using Nital etching is nearly impossible. Nital etching is good at specific phase analysis than LePera etching when using SEM images.

Development of an Automated ESG Document Review System using Ensemble-Based OCR and RAG Technologies

  • Eun-Sil Choi
    • Journal of the Korea Society of Computer and Information
    • /
    • v.29 no.9
    • /
    • pp.25-37
    • /
    • 2024
  • This study proposes a novel automation system that integrates Optical Character Recognition (OCR) and Retrieval-Augmented Generation (RAG) technologies to enhance the efficiency of the ESG (Environmental, Social, and Governance) document review process. The proposed system improves text recognition accuracy by applying an ensemble model-based image preprocessing algorithm and hybrid information extraction models in the OCR process. Additionally, the RAG pipeline optimizes information retrieval and answer generation reliability through the implementation of layout analysis algorithms, re-ranking algorithms, and ensemble retrievers. The system's performance was evaluated using certificate images from online portals and corporate internal regulations obtained from various sources, such as the company's websites. The results demonstrated an accuracy of 93.8% for certification reviews and 92.2% for company regulations reviews, indicating that the proposed system effectively supports human evaluators in the ESG assessment process.

A Study on Fast Iris Detection for Iris Recognition in Mobile Phone (휴대폰에서의 홍채인식을 위한 고속 홍채검출에 관한 연구)

  • Park Hyun-Ae;Park Kang-Ryoung
    • Journal of the Institute of Electronics Engineers of Korea SP
    • /
    • v.43 no.2 s.308
    • /
    • pp.19-29
    • /
    • 2006
  • As the security of personal information is becoming more important in mobile phones, we are starting to apply iris recognition technology to these devices. In conventional iris recognition, magnified iris images are required. For that, it has been necessary to use large magnified zoom & focus lens camera to capture images, but due to the requirement about low size and cost of mobile phones, the zoom & focus lens are difficult to be used. However, with rapid developments and multimedia convergence trends in mobile phones, more and more companies have built mega-pixel cameras into their mobile phones. These devices make it possible to capture a magnified iris image without zoom & focus lens. Although facial images are captured far away from the user using a mega-pixel camera, the captured iris region possesses sufficient pixel information for iris recognition. However, in this case, the eye region should be detected for accurate iris recognition in facial images. So, we propose a new fast iris detection method, which is appropriate for mobile phones based on corneal specular reflection. To detect specular reflection robustly, we propose the theoretical background of estimating the size and brightness of specular reflection based on eye, camera and illuminator models. In addition, we use the successive On/Off scheme of the illuminator to detect the optical/motion blurring and sunlight effect on input image. Experimental results show that total processing time(detecting iris region) is on average 65ms on a Samsung SCH-S2300 (with 150MHz ARM 9 CPU) mobile phone. The rate of correct iris detection is 99% (about indoor images) and 98.5% (about outdoor images).