• The Journal of the Korea institute of electronic communication sciences
• /
• v.8 no.9
• /
• pp.1319-1324
• /
• 2013

The mean shift algorithm has achieved considerable success in object tracking due to its simplicity and robustness. It finds local minima of a similarity measure between the color histograms or kernel density estimates of the target and candidate image. However, it is sensitive to the noises due to objects or background having similar color distributions. In addition, occlusion by another object often causes a face region to change in size and position although a face region is a critical clue to perform face recognition or compute face orientation. We assume that depth and color are effective to separate a face from a background and a face from objects, respectively. From the assumption we devised a bilateral filter using color and depth and incorporate it into the mean-shift algorithm. We demonstrated the proposed method by some experiments.

• The Journal of the Acoustical Society of Korea
• /
• v.38 no.1
• /
• pp.128-138
• /
• 2019

In this paper, we present fusion methods for two different lofargrams. Since the conventional method synthesizes the lofargrams using frequency spectrum, it has limited performance in fusion of tonal signals which have two-dimensional information of the time-frequency domain. Proposed algorithm uses a two-dimensional directional bilateral filter for preprocessing and fuses two lofargrams based on comparison of local anisotropy of the lofargrams. After noise is suppressed and tonals are sharpened, the local anisotropy can be used as a criterion to divide tonals and noise. The experiment results using simulated data and real data showed that the proposed algorithms result in similar or lower noise level of the fused lofargram than conventional algorithms and decrease tonal omission in fusion process.

• Journal of Korea Society of Industrial Information Systems
• /
• v.23 no.6
• /
• pp.21-27
• /
• 2018

Wearing degree and uneven wearing detection algorithm using horizontal edge information is proposed in this paper. The noise in the input image is removed by bilateral filter, and then edges are extracted from the filtered image by using the proposed mask. As the tire is worn, grooves of tire shoulder or sipes are changed more than the vertical grooves. Therefore the edges from grooves of tire shoulder or sipes have more information about the tire wearing than the edges from vertical grooves. Proposed mask that is reflected this feature is used to extract the horizontal edges. After edge extraction, the edge image is represented in two-level system. The edge pixels of the binarization image are used to decide the wearing degree and uneven wearing. This proposed method can be used easily without any other equipments. The proposed method is conducted with a real vehicle, and the experimental results show the good performance of the proposed method in detecting wearing degree and uneven wearing.

• Proceedings of the Korean Information Science Society Conference
• /
• 2003.04a
• /
• pp.821-823
• /
• 2003

지금까지의 TV 방송 서비스는 지상파. 위성 또는 케이블 방송국에서 제공되는 방송 프로그램을 단순히 수동적으로 시청하는 형태가 주를 이루었다. 그러나 최근 디지털 기술의 발전으로 이러한 단 방향 TV방송 서비스를 넘어 양방향 TV 방송 서비스를 가능하게 함으로써 정보 공급자와 사용자 간의 수평적 커뮤니케이션이 가능하게 되었다. 또한 다매체 다채널 방송 환경의 도래로 인하여 TV 시청자에게 수많은 방송 프로그램 정보가 제공됨으로써 정보의 과부하로 인하여 방송 프로그램의 수동적 취사선택이 매우 어려운 TV시청 환경으로 바뀌고 있다. 이로 인하여 TV 시청자의 선호도에 기반한 방송 프로그램 시청환경 제공의 필요성이 대두되었으며 이러한 필요성은 TV의 개인화된 맞춤형 방송 서비스의 도래를 예고 하고 있다. 본 논문에서는 사용자의 요구와 선호도에 따라 개인화된 정보를 전자 프로그램 가이드, 퍼스널 캐스팅 또는 검색/필터링 등의 응용에 사용할 수 있도록 하는 MPEG-21의 컨텍스트 디지털 아이템에 대한 연구이다.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.49 no.2
• /
• pp.35-44
• /
• 2012

Most recent infrared (IR) sensors have a focal-plane array (FPA) structure. Spatial non-uniformity of a FPA structure, however, introduces unwanted fixed pattern noise (FPN) to images. This non-uniformity correction (NUC) of a FPA can be categorized into target-based and scene-based approaches. In a target-based approach, FPN can be separated by using a uniform target such as a black body. Since the detector response randomly drifts along the time axis, however, several scene-based algorithms on the basis of a video sequence have been proposed. Among those algorithms, the state-of-the-art one based on Kalman filter uses one-directional warping for motion compensation and only compensates for offset non-uniformity of IR camera detectors. The system model using one-directional warping cannot correct the boundary region where a new scene is being introduced in the next video frame. Furthermore, offset-only correction approaches may not completely remove the FPN in images if it is considerably affected by gain non-uniformity. Therefore, for FPN reduction in IR videos, we propose a joint correction algorithm of gain and offset based on bi-directional warping. Experiment results using simulated and real IR videos show that the proposed scheme can provide better performance compared with the state-of-the art in FPN reduction.