• Current Optics and Photonics
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• v.8 no.5
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• pp.463-471
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• 2024

Multimode fibers (MMFs) possess high information throughput and small core diameter, making them highly promising for applications such as endoscopy and communication. However, modal dispersion hinders the direct use of MMFs for image transmission. By training neural networks on time-series waveforms collected from MMFs it is possible to reconstruct images, transforming blurred speckle patterns into recognizable images. This paper proposes a fully convolutional neural-network model, MSMDFNet, for image restoration in MMFs. The network employs an encoder-decoder architecture, integrating multiscale convolutional modules in the decoding layers to enhance the receptive field for feature extraction. Additionally, attention mechanisms are incorporated from both spatial and channel dimensions, to improve the network's feature-perception capabilities. The algorithm demonstrates excellent performance on MNIST and Fashion-MNIST datasets collected through MMFs, showing significant improvements in various metrics such as SSIM.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.11
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• pp.911-920
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• 2018

In this study, we performed a study to track the angle between the guided weapon and the target by using the strap-down image seeker, and constructed a test bed that can simulate it visually. This paper describes a method to maintain high-performance feature distribution in the implementation of sparse feature tracking algorithm such as Lucas Kanade's optical flow algorithm for target tracking using image information. We have extended the feature tracking problem to the concept of feature management. To realize this, we constructed visual environment using Unity3D engine and developed image processing simulation using OpenCV. For the co-simulation, dynamic system modeling was performed with Matlab Simulink, the visual environment using Unity3D was constructed, and computer vision work using OpenCV was performed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.5
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• pp.470-475
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• 2009

This paper is the study which is head tracker using pattern matching. Proposal algorithm obtains initial attitude of head tracker using pattern matching. Optical head tracker consists of infrared LEDs(features) which are attached helmet as pattern, stereo infrared cameras. Proposal algorithm analyzes patterns by error rate of feature distance and estimates feature characteristic number. Initial attitude of head tracker is obtained to compare map data and feature characteristic number.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.10
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• pp.95-104
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• 1993

IPA(interpattern association) model is a method of feature extraction using a neural network. Even in the case that the reference patterns are simuklar to one another, this model can recover the reference patterns effectively. However, when the pattern whose feature pixels are lost is used as input, this model can not guarantee perfect recovery of the reference pattern. It is proposed a improved interpattern association(IPA) model for the feature extraction using neural network. The improved IPA model that combines the first interconnection weight matrix of the IPA model with the second additional weight matrix is proposed here to overcome the recovery problem of the original IPA model. The results of computer simulation and optical experiment are advanced.

• Bulletin of the Korean Chemical Society
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• v.34 no.3
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• pp.759-762
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• 2013

Four prominent features of Titan's haze are found within the '3.4-${\mu}m$' absorption to be uniform with recent vertically resolved Cassini/VIMS spectra. These are absorptions at 2998 $cm^{-1}$ (3.34 ${\mu}m$), 2968 $cm^{-1}$ (3.37 ${\mu}m$), 2927 $cm^{-1}$ (3.42 ${\mu}m$), and 2882 $cm^{-1}$ (3.47 ${\mu}m$). A detailed fitting suggests that the 2998 $cm^{-1}$ feature could originate from amorphous acetonitrile ($CH_3CN$) carrying about 25% of integrated optical depth; the remaining features, which account for 75% of the integrated optical depth, could arise from a distinct triplet (C-H stretching) structure of radiolyzed hydrocarbons. An additional feature was possibly evidenced at altitudes higher than 300 km and attributable to 'polymer-capped' methane ($CH_4$), significantly constraining the chemical composition of organic haze layers under Titan's active radiation field.

• The Journal of Korea Robotics Society
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• v.8 no.4
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• pp.266-272
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• 2013

Facial feature extraction and tracking are essential steps in human-robot-interaction (HRI) field such as face recognition, gaze estimation, and emotion recognition. Active shape model (ASM) is one of the successful generative models that extract the facial features. However, applying only ASM is not adequate for modeling a face in actual applications, because positions of facial features are unstably extracted due to limitation of the number of iterations in the ASM fitting algorithm. The unaccurate positions of facial features decrease the performance of the emotion recognition. In this paper, we propose real-time facial feature extraction and tracking framework using ASM and LK optical flow for emotion recognition. LK optical flow is desirable to estimate time-varying geometric parameters in sequential face images. In addition, we introduce a straightforward method to avoid tracking failure caused by partial occlusions that can be a serious problem for tracking based algorithm. Emotion recognition experiments with k-NN and SVM classifier shows over 95% classification accuracy for three emotions: "joy", "anger", and "disgust".

• The KIPS Transactions:PartB
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• v.16B no.2
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• pp.109-116
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• 2009

In this thesis, an object tracking method based on the active feature model and the optical flow in stereo images is proposed. We acquired the translation information of object of interest and the features of object by utilizing the geometric information and depth of stereo images. Tracking performance is improved for the occlude object with this information by predicting the movement information of features of the occlude object. Rigid and non-rigid objects are experimented. From the result of experiment, the OOI can be real-time tracked from complicate back ground. Besides, we got the improved result of object tracking in any occlusion state, no matter what it is rigid or non-rigid object.

• Journal of the Optical Society of Korea
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• v.14 no.4
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• pp.316-320
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• 2010

We report an application of full-field optical coherence tomography (FF-OCT) for identifying counterfeit bank notes. The depth-resolved imaging capability of FF-OCT was used for tomographic identification of superficially-identical objects. By retrieving the internal structures of the security feature (cash hologram) of an original banknote, we could demonstrate the feasibility of FF-OCT to identify counterfeit money. The FF-OCT images showed that the hologram consisted of micron scale multi-coated layers including an air gap. Therefore, it is expected that FF-OCT has potential as a new non-invasive tool to discern imitation of currency, and it would find applications in a wide field of counterfeit sciences.

• International Journal of Contents
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• v.4 no.2
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• pp.24-28
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• 2008

In this paper, we propose a new approach for content-based video retrieval using non-parametric based motion classification in the shot-based video indexing structure. Our system proposed in this paper has supported the real-time video retrieval using spatio-temporal feature comparison by measuring the similarity between visual features and between motion features, respectively, after extracting representative frame and non-parametric motion information from shot-based video clips segmented by scene change detection method. The extraction of non-parametric based motion features, after the normalized motion vectors are created from an MPEG-compressed stream, is effectively fulfilled by discretizing each normalized motion vector into various angle bins, and by considering the mean, variance, and direction of motion vectors in these bins. To obtain visual feature in representative frame, we use the edge-based spatial descriptor. Experimental results show that our approach is superior to conventional methods with regard to the performance for video indexing and retrieval.

• The Transactions of the Korea Information Processing Society
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• v.1 no.3
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• pp.311-318
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• 1994

In this paper, a new stroke extraction method of Chinese character base on the human optical field(the Receptive Field of Cell) is proposed. In processing the feature extraction of the chinese character, needed are more perfect extraction methods for separated informations and its data base. This method can be applied to processing neural cell using conventional feature extraction mechanism in the optical boundary of retina and cerebrum. With this method, its applicability and effectiveness were demonstrated extracting strokes from Chinese character.