• Korean Journal of Remote Sensing
• /
• v.29 no.5
• /
• pp.487-497
• /
• 2013

In this paper, a method of using high resolution stereo images is proposed to efficiently detect DSM errors. Automatically generated DSMs from stereo matching can be a useful solution to acquire DSM data in various aspects but they may include many gross errors coming from automatic processing. Therefore, a method to detect the gross errors on DSM is required for efficient DSM update. In this paper, stereo analysis using high resolution stereo images was investigated to represent reliability of DSM grids. The analysis enabled automatic detection of the gross errors which greatly influenced DSM quality. We used the reference DSM to assess reliability of our proposed method. We confirmed from experimental results that our method can be a valuable DSM errors analysis for efficient DSM correction. Our method is useful to analyze and improve DSM accuracy for various types of DSM and DEM. It is expected that our approach can be exploited for achievement of reliable DSM and DEM.

• Journal of Veterinary Clinics
• /
• v.15 no.2
• /
• pp.450-454
• /
• 1998

These studies were performed to find out the possibility of automatic detection of the diseased animal with fever by farmers themselves. Firstly, the body temperature of 331 dairy cows was investigated according to major disease symptoms manifested. Secondly, AD 590 thermometer was used to take the teat temperature of the milking cows to determine the possibility of automatic taking of body temperature while milking. The temperatures of scapha of ear and coccygeal artery part were also taken fur the non-milking dairy cows and Korean native cowl 1. The average body temperature of dairy cows associated with respiratory diseases puerperal disease, or mastitis was higher than normal temperature denoting respectively 39.8,39.6, and $39.3{\circ}C.2.$ The teat temperaure of the milking dairy cows with fever($39.5~39.6{\circ}C$) and the cows with mastitis was respectively 1.02 and 0.56${\circ}C$ higher than that of normal cows. 3. The average teat temperature taken by AD 590 was 33.91, 34.93, and 34.50${\circ}C$ in normal milking dairy cows, cows with fever(39.5~39.6${\circ}C$), and cows with mastitis, respectively. 4. The mean temperatures at scapha and coccygeal part of non-milking dairy cows and Korean native cows were 35.62 and 36.63${\circ}C$, respectively. It was concluded that AD 590 thermometer would be usable for the farmers to automatirally detect the body temperature of dairy cows while milking and subsquently to find the diseased cow with fever and that the scapha of ear and coccygeal artery part of the cattle could be the body parts of simply detecting body temperature of non-milking cattle.

• The Korean Journal of Cytopathology
• /
• v.5 no.1
• /
• pp.15-22
• /
• 1994

Cancer of the cervix is the most common malignancy in women in developing countries and the second most common cancer in women throughout the world with approximately 500,000 new cases each year. Prevention of this large number of premature deaths among women is, therefore, a goal worthy of urgent and serious consideration. Due to its high diagnostic disagreement among pathologists and large quantity of specimens, it is necessary to develop an automatic screening system measuring morphologic and densitometric features of the samples. Many research works have been published but most of them used Feulgen stained specimens which are not a usual staining method used in clinics. In this thesis, an automatic cancerous nucleus detection method essential to a screening system with papanicolaou stained specimens called Pap-smear is proposed which employs image processing techniques. It uses edge information to segment objects and morphologic as well as densitometric information to distinguish cancerous nuclei from dirts or normal nuclei. It has produced useful results in our study.

• Journal of Korean Society for Geospatial Information Science
• /
• v.19 no.1
• /
• pp.79-86
• /
• 2011

Recently, aerial laser scanning technology has received full attention in constructing DEM(Digital Elevation Model). It is well known that the quality of DEM is mostly influenced by the accuracy of DTD(Digital Terrain Data) extracted from LiDAR(Light Detection And Ranging) raw data. However, there are always misclassified data in the DTD generated by automatic filtering process due to the limitation of automatic filtering algorithm and intrinsic property of LiDAR raw data. In order to eliminate the misclassified data, a manual filtering process is performed right after automatic filtering process. In this study, an algorithm that detects automatically possible misclassified data included in the DTD from automatic filtering process is proposed, which will reduce the load of manual filtering process. The algorithm runs on 2D grid data structure and makes use of several parameters such as 'Slope Angle', 'Slope DeltaH' and 'NNMaxDH(Nearest Neighbor Max Delta Height)'. The experimental results show that the proposed algorithm quite well detected the misclassified data regardless of the terrain type and LiDAR point density.

• Proceedings of the IEEK Conference
• /
• 2002.06c
• /
• pp.211-214
• /
• 2002

Automatic video partitioning is the first step for content-based indexing and retrieval of video data. In this paper, an efficient algorithm for scene change detection is proposed, where cumulative histogram and edge information are utilized. Experimental results have shown the effectiveness of the proposed algorithm.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.13 no.6
• /
• pp.321-328
• /
• 2018

This paper presents an automatic target tracking flight system using a PID controller based on velocity command of a multirotor UAV. The automatic flight system includes marker based onboard target detection and an automatic velocity command generation replacing manual controller. A quad-rotor UAV is equipped with a camera and an image processing computer to detect the marker in real time and to estimate the relative distance from the target. The marker tracking system consists of PID controller and generates velocity command based on the relative distance. The generated velocity command is used as the input of the UAV's original flight controller. The operation of the proposed system was verified through actual flight tests using a marker on top of a moving vehicle and tracks it to successfully demonstrate its capability using a quad-rotor UAV.

• Proceedings of the KOR-KST Conference
• /
• 1999.10a
• /
• pp.167-172
• /
• 1999

• JOURNAL OF ELECTRICAL WORLD
• /
• no.2 s.146
• /
• pp.11-18
• /
• 1989

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
• /
• 2002.11a
• /
• pp.178-183
• /
• 2002

• The Journal of the Acoustical Society of Korea
• /
• v.17 no.2E
• /
• pp.38-46
• /
• 1998

In this paper, we propose a remote speech input device, a new method of user-friendly speech input in spontaneous speech recognition system. We focus the user friendliness on hands-free and microphone independence in speech recognition applications. Our method adopts two algorithms, the automatic speech detection and the microphone array delay-and-sum beamforming (DSBF)-based speech enhancement. The automatic speech detection algorithm is composed of two stages; the detection of speech and nonspeech using the pitch information for the detected speech portion candidate. The DSBF algorithm adopts the time domain cross-correlation method as its time delay estimation. In the performance evaluation, the speech detection algorithm shows within-200 ms start point accuracy of 93%, 99% under 15dB, 20dB, and 25dB signal-to-noise ratio (SNR) environments, respectively and those for the end point are 72%, 89%, and 93% for the corresponding environments, respectively. The classification of speech and nonspeech for the start point detected region of input signal is performed by the pitch information-base method. The percentages of correct classification for speech and nonspeech input are 99% and 90%, respectively. The eight microphone array-based speech enhancement using the DSBF algorithm shows the maximum SNR gaing of 6dB over a single microphone and the error reductin of more than 15% in the spontaneous speech recognition domain.