• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.415-420
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• 2009

For the emergency detecting in general CCTV environment of our daily life, the monitoring by only images through CCTV information occurs some problems especially in cost as well as man power. Therefore, in this paper, for detecting emergency state dynamically through CCTV as well as resolving some problems, we propose our advanced speech recognition system. For the purpose of it, we adopt HMM(Hidden Markov Model) in our system to do a feature extraction. Also, we adopt Wiener filter technique for noise elimination in many information coming from on CCTV environment. In this paper, our system send only the emergency speech information to a manager to deal with emergency state effectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.4
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• pp.854-860
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• 2004

The result of fingerprint matching is different as the quality or the state of input fingerprint image. We can extract the false direction information when the quality of fingerprint is degraded by the noise or the scars of the ridges. The information of the direction is very important for the elimination of the false minutia, the measurement of the ridge distance, matching, finding of cores and deltas. We need the method which can compensate or correct the false information of directions because the false directions include serious errors in the fingerprint recognition. We propose a method which can compensate or correct the false direction of fingerprint with a \alpha$-trimmed mean filter followed by LPF to reconstruct the false direction information when fingerprints are corrupted by scars.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.4
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• pp.237-242
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• 2022

Acquiring high-quality images in control and measurement systems is one of the important factors. Among image acquisition technologies, SFF (Shape from Focus) is a technology for recovering a 3D shape by acquiring 2D images with different focus levels by moving an object at a predetermined step size along the optical axis. For SFF, when an object is moved at a constant step size, mechanical vibration, referred as jitter noise, occurs in each step along the optical axis. In this paper, a new state estimation filter is designed and applied for reducing the jitter noise. For the application of the proposed method, the jitter noise and focus curves are modeled as Gaussian function. Experimental results demonstrate the effectiveness of proposed method.

• Journal of radiological science and technology
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• v.30 no.1
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• pp.1-6
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• 2007

This study is to decrease compound noise in x-ray films. This study compared Signal to noise ratio(SNR), Peak signal to noise ratio(PSNR), Mean square error(MSE) to surface of the earth. In addition, we evaluated noise elimination effect according to the kernel size of Median filter. This experiments show that some filters are useful by finding image that is near in circle image comparing circle picture with each processed picture. In noise power value, when cutoff frequency was compared with other filters of cutoff frequency. Cutoff frequency of $2/3\pi{\sim}3/4\pi$ is good and it shows good SNR and PSNR. Therefore, it can display high filter effect. As Median Filter's Kernel size grows SNR value gets bigger, which shows better filter effect. Most pictures are distorted after filter application in medical treatment image. It is important to keep spatial resolution in most medical images. Visual estimation as well as quantitative indicators should be necessary for a better image.

• Journal of Advanced Navigation Technology
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• v.3 no.2
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• pp.97-107
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• 1999

Passive sensors such as Laser Range Finder(LRF) and Forward Looking Infrared(FLIR) camera frequently used for tracking aircraft landing produce the measurements of elevation angle contaminated by large noise due to the exhaust plume disturbance. This results in poor tracking performance if the extended Kalman filter is used for estimation of the range and elevation which are corrupted by the non-Gaussian noise such as plume disturbance. In this paper, an adaptive estimation filter and the extended Kalman filter is combined to produce a combination-type filter. In this approach the adaptive filter is used for the plume-type disturbance noise and the extended Kalman filter is utilized for the measurement of Gaussian type. The proposed combination filter is effective for the trajectory estimation of landing aircraft under the influence of unknown bias and numerical simulations illustrate the performance of the proposed filter.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.12
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• pp.41-50
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• 1999

In this paper, the new VLSI architecture of a reconstruction filter for morphological image segmentation is proposed. The filter, based on the $h_{max}$ operation, simplifies the interior of each region while preserving the boundary information. The proposed architecture adopts a partitioned memory structure and an efficient image scanning strategy to reduce the operations. The proposed memory partitioning scheme makes it possible that every data required for processing can be read from each memory at a time, resulting in parallel data processing. By the extended connectivity consideration, the operation is much decreased because more simplification is achieved in scanning stage. The selective raster scan strategy endows the satisfactory noise removal capability with negligible hardware complexity increase. The proposed architecture is designed using VHDL, and functional evaluation is performed by the CAD tool, Mentor. The experiment results show that the proposed architecture can simplify image profile with less than 18% operations of the conventional method.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.3
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• pp.26-31
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• 1999

In this paper, we propose a facial characteristic detection algorithm based on knowledge and object segmentation method for image communication. In this algorithm, under the condition of the same lumination and distance from the fixed video camera to human face, we capture input images of 256 $\times$ 256 of gray scale 256 level and then remove the noise using the Gaussian filter. Two images are captured with a video camera, One contains the human face; the other contains only background region without including a face. And then we get a differential image between two images. After removing noise of the differential image by eroding End dilating, divide background image into a facial image. We separate eyes, ears, a nose and a mouth after searching the edge component in the facial image. From simulation results, we have verified the efficiency of the Proposed algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.3
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• pp.61-69
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• 2007

This paper proposes new preprocessing algorithm to extract minutiae in the process of fingerprint recognition. Fingerprint images quality enhancement is a topic phase to ensure good performance in a topic phase to ensure good performance in a Automatic Fingerprint Identification System(AFIS) based on minutiae matching. This paper proposes an algorithm to improve fingerprint image preprocessing to extract minutiae accurately based on directional filter. We improved the suitability of low quality fingerprint images to better suit fingerprint recognition by using valid ridge vector and ridge probability of fingerprint images. With the proposed fingerprint improvement algorithm, noise is removed and presumed ridges are more clearly ascertained. The algorithm is based on five step: computation of effective ridge vector, computation of ridge probability, noise reduction, ridge emphasis, and orientation compensation and frequency estimation. The performance of the proposed approach has been evaluated on two set of images: the first one is self collected using a capacitive semiconductor sensor and second one is DB3 database from Fingerprint Verification Competition (FVC).

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.494-499
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• 2012

In this paper, a new method for detecting various objects that can be risks to safety navigation in sea environment is proposed. By analysing Infrared(IR) images obtained from various sea environments, we could find out that object regions include both horizontal and vertical direction edges while background regions of sea surface mainly include vertical direction edges. Therefore, we present an approach to detecting object regions considering horizontal and vertical edges. To this end, in the first step, image enhancement is performed by suppressing noises such as sea glint and complex clutters using a statistical filter. In the second step, a horizontal edge map and a vertical edge map are generated by 1-D Discrete Cosine Transform technique. Then, a combined map integrating the horizontal and the vertical edge maps is generated. In the third step, candidate object regions are detected by a adaptive thresholding method. Finally, exact object regions are extracted by eliminating background and clutter regions based on morphological operation.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.04a
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• pp.92-95
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• 2003

초전형 센서의 특성 평가 방법에는 여러 가지 방법들이 존재하며, 이에 대한 표준화된 특성 평가방법의 개발이 필요로 한다. 측정 평가의 방법이나 조건 등에 따라서 평가 결과가 크게 변할 수 있는 사항들이며, 따라서 국내 뿐 아니라 대외적으로 다른 나라의 제품들과 신뢰성을 가지고 경쟁을 하기 위해서는 평가항목이나 평가방법의 표준화가 절실하게 요구된다. 초전형 적외선 센서를 평가하는 항목에는 기본적으로 입력에 대한 출력신호의 크기를 평가하는 감도(responsivity), 잡음과 관련되어 센서가 검출할 수 있는 최소의 신호를 나타내는 NEP(Noise Equivalent Power)와 이것을 센서의 감지 면적으로 정규화 시킨 검출능(detectivity), 응답 속도를 나타내는 시정수(time constant)가 있으며 이러한 항목들이 표준화의 대상이 된다. 본 실험에서는 기존의 상용화된 센서들을 가지고 초전형 적외선 센서의 특성을 측정 하였다. 특성을 측정할 때 다른 요인들 보다 노이즈로 인한 영향이 상당히 크므로 측정시 노이즈 발생 문제를 해결하는 방법으로 본 논문에서는 센서 측정에 사용되는 증폭 회로에서 노이즈를 해결하려고 하였다. 우리는 증폭 회로구성에서 노이즈를 제거하기 위해서 신호입력단과 전압 압력에 잡음제거 필터로 R, C를 사용하였다. 회로설계로 제작된 증폭회로와 측정 장치를 가지고 측정을 한 결과 센서의 감도는 $3.0mV_{p-p}$, 응답시간은 20ms정도의 값으로 가장 일반적인(typical) 값을 보인다.