• Journal of Korea Spatial Information System Society
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• v.10 no.2
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• pp.49-62
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• 2008

This paper proposes an indoor location positioning system for the image recognition based LBS. The proposed system is a vision-based location positioning system that is implemented the augmented reality by overlaying the location results with the view of the user. For implementing, the proposed system uses the pattern matching and location model to recognize user location from images taken by a wearable mobile PC with camera. In the proposed system, the system uses the pattern matching and location model for recognizing a personal location in image sequences. The system is estimated user location by the image sequence matching and marker detection methods, and is recognized user location by using the pre-defined location model. To detect marker in image sequences, the proposed system apply to the adaptive thresholding method, and by using the location model to recognize a location, the system can be obtained more accurate and efficient results. Experimental results show that the proposed system has both quality and performance to be used as an indoor location-based services(LBS) for visitors in various environments.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.93-101
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• 2011

For mobile robot, recognizing its current location is very important to navigate autonomously. Especially, loop closing detection that robot recognize location where it has visited before is a kernel problem to solve localization. A considerable amount of research has been conducted on loop closing detection and localization based on appearance because vision sensor has an advantage in terms of costs and various approaching methods to solve this problem. In case of scenes that consist of repeated structures like in corridors, perceptual aliasing in which, the two different locations are recognized as the same, occurs frequently. In this paper, we propose an improved method to recognize location in the scenes which have similar structures. We extracted salient regions from images using visual attention model and calculated weights using distinctive features in the salient region. It makes possible to emphasize unique features in the scene to classify similar-looking locations. In the results of corridor recognition experiments, proposed method showed improved recognition performance. It shows 78.2% in the accuracy of single floor corridor recognition and 71.5% for multi floor corridors recognition.

• The Journal of the Korea Contents Association
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• v.11 no.2
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• pp.31-39
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• 2011

The facial recognition algorithms using Gabor wavelet based face graph produce very good performance while they have some weakness such as a large amount of computation and an irregular result depend on initial location. We proposed a fully automatic facial recognition algorithm using a Gabor feature based geometric deformable face graph matching. The initial location and size of a face graph can be selected using Adaboost detection results for speed-up. To find the best face graph with the face model graph by updating the size and location of the graph, the geometric transformable parameters are defined. The best parameters for an optimal face graph are derived using an optimization technique. The simulation results show that the proposed algorithm can produce very good performance with recognition rate 96.7% and recognition speed 0.26 sec for FERET database.

• Korean Journal of Optics and Photonics
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• v.14 no.1
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• pp.51-57
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• 2003

The hologram of an object contains the information of the object's depth distribution as well as the depth location of the object. However these pieces of information are blended together as a form of fringe pattern. This makes it hard to extract the depth location of the object directly from the hologram. In this paper, I propose a numerical method which separates the depth location information from the single-sideband hologram by gaussian low-pass filtering. The depth location of the object is extracted by numerical analysis of the filtered hologram. The hologram at the object's depth location is recovered by the extracted depth location.

• International Journal of Knowledge Content Development & Technology
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• v.7 no.1
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• pp.101-120
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• 2017

Healthcare professionals have edited many health questions (HQs) and their answers for healthcare consumers on the Internet. The HQs provide both readable and reliable health information, and hence retrieval of those HQs that are relevant to a given question is essential for health education and promotion through the Internet. However, retrieval of relevant HQs needs to be based on the recognition of the intention of each HQ, which is difficult to be done by predefining syntactic and semantic rules. We thus model the intention recognition problem as a text classification problem, and develop two techniques to improve a learning-based text classifier for the problem. The two techniques improve the classifier by location-based and area-based feature weightings, respectively. Experimental results show that, the two techniques can work together to significantly improve a Support Vector Machine classifier in both the recognition of HQ intentions and the retrieval of relevant HQs.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.108-110
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• 2004

Automatic license plate recognition (LPR) is one of the critical techniques of the intelligent transportation system (ITS), in which license plate location plays an important role. In this paper, through surveying the international existing techniques, a new method for locating license plate is proposed: utilize row scan method to locate up and down boundary of the plate; and based on the location of up and down boundary, take advantage of the feature of plate area to locate left and right boundary of the plate. The tests of using the proposed algorithms have been conducted. The experimental results show that the proposed approaches are reasonable and accurate.

• Journal of Ship and Ocean Technology
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• v.12 no.3
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• pp.26-35
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• 2008

Recognition of real time locations of crews for a naval ship is important, not only for the operation efficiency but also for the safety of onboard crews in the ship. More than 100 crews are dwelling in a modem naval ship and they are involved in various duties. Moreover many visitors come in and out frequently while the ship is moored in a harbor. It sometimes requires considerable time and efforts to find a person for urgent mission. It would enhance the operational efficiency if locations of onboard crews are recognized and monitored in real time. An active type RFID tag, which has a specific ID number, is distributed to each crew member, which should be carried during his stay in the ship. A number of fixed type RFID readers are to be located at the major passages of the ship, which are connected to the main computer via Local Area Network. The location of a crew would be identified by the ID number of his RFID tag and the location of the RFID reader which detected the RFID tag. A middleware is needed to process the collected data in the main computer. The data is fed to application softwares, which actually display locations of the concerned crews. The software is coded using GUI (Graphic User Interface) for better user friendliness, which has the function of storing the location history of a crew, and sending warning messages to appropriate persons, if unallowable behavior is detected. An auxiliary naval ship is selected for an experimental application study of the proposed system. It turns out that the required budget and time for the realization of the system is within the allowable limits. But complementary measures to protect the privacy of onboard crews should be considered and adopted, before the application of the system is realized.

• The KIPS Transactions:PartB
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• v.17B no.1
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• pp.1-8
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• 2010

The researches about gaze recognition which current user gazes and finds the location have increasingly developed to have many application. The gaze recognition of existence all about researches have got problems because of using equipment that Infrared(IR) LED, IR camera and head-mounted of high price. This study propose and implement the gaze recognition system based on SVM using a single PC Web camera. The proposed system that divide the gaze location of 36 per 9 and 4 to recognize gaze location of 4 direction and 9 direction recognize user's gaze. Also, the proposed system had apply on image filtering method using difference image entropy to improve performance of gaze recognition. The propose system was implements experiments on the comparison of proposed difference image entropy gaze recognition system, gaze recognition system using eye corner and eye's center and gaze recognition system based on PCA to evaluate performance of proposed system. The experimental results, recognition rate of 4 direction was 94.42% and 9 direction was 81.33% for the gaze recognition system based on proposed SVM. 4 direction was 95.37% and 9 direction was 82.25%, when image filtering method using difference image entropy implemented. The experimental results proved the high performance better than existed gaze recognition system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.769-786
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• 2016

Object recognition and object location have always drawn much interest. Also, recently various computational models have been designed. One of the big issues in this domain is the lack of an appropriate model for extracting important part of the picture and estimating the object place in the same environments that caused low accuracy. To solve this problem, a new Salient Based Bag of Visual Word (SBBoVW) model for object recognition and object location estimation is presented. Contributions lied in the present study are two-fold. One is to introduce a new approach, which is a Salient Based Bag of Visual Word model (SBBoVW) to recognize difficult objects that have had low accuracy in previous methods. This method integrates SIFT features of the original and salient parts of pictures and fuses them together to generate better codebooks using bag of visual word method. The second contribution is to introduce a new algorithm for finding object place based on the salient map automatically. The performance evaluation on several data sets proves that the new approach outperforms other state-of-the-arts.

• Journal of IKEEE
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• v.25 no.1
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• pp.25-31
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• 2021

The conventional credit card number recognition system generally needs a card to be placed in a designated location before its processing, which is not an ideal user experience especially for people with visual impairment. To improve the user experience, this paper proposes a novel algorithm that can automatically detect the location of a credit card number based on the fact that a group of sixteen digits has a fixed aspect ratio. The proposed algorithm first performs morphological operations to obtain multiple candidates of the credit card number with >4:1 aspect ratio, then recognizes the card number by testing each candidate via OCR and BIN matching techniques. Implemented with OpenCV and Firebase ML, the proposed scheme achieves 77.75% accuracy in the credit card number recognition task.