• KIPS Transactions on Software and Data Engineering
• /
• v.3 no.7
• /
• pp.277-284
• /
• 2014

The detection method of curves for the lanes which is powerful for the variation by utilizing the lane variation vector and cardinal spline on the inverse perspective transformation screen images which do not required the camera parameters are suggested in this paper. This method detects the lane area by setting the expected lane area in the s frame and next s+1 frame where the inverse perspective transformation and entire process of the lane filter are adapted, and expects the points of lane location in the next frames with the lane variation vector calculation from the detected lane areas. The scan area is set from the nextly expected lane position and new lane positions are detected within these areas, and the lane variation vectors are renewed with the detected lane position and the lanes are detected with application of cardinal spline for the control points inside the lane areas. The suggested method is a powerful method for curved lane detection, but it was adopted to the linear lanes too. It showed an excellent lane detection speed of about 20ms in processing a frame.

• Journal of Korea Multimedia Society
• /
• v.5 no.4
• /
• pp.415-425
• /
• 2002

In this paper, we present a content-based image retrieval method which is based on the feature extraction in the wavelet transform domain. In order to overcome the drawbacks of the feature vector making up methods which use the global wavelet coefficients in subbands, we utilize the energy value of wavelet coefficients, and the shape-based retrieval of objects is processed by moment which is invariant in translation, scaling, rotation of the objects The proposed methods reduce feature vector size, and make progress performance of classification retrieval which provides fast retrievals times. To offer the abilities of region-based image retrieval, we discussed the image segmentation method which can reduce the effect of an irregular light sources. The image segmentation method uses a region-merging, and candidate regions which are merged were selected by the energy values of high frequency bands in discrete wavelet transform. The region-based image retrieval is executed by using the segmented region information, and the images are retrieved by a color, texture, shape feature vector.

• The Journal of the Korea Contents Association
• /
• v.3 no.1
• /
• pp.9-13
• /
• 2003

We propose a block motion estimation algorithm based on a statistical image feature for video sequences. The statistical feature of the reference block is obtained, then applied to select the candidate starting points (SPs) in the regular starting points pattern (SPP) by comparing the statistical feature of reference block with that of blocks which are spread ower regular SPP. The final SPs are obtained by their Mean Absolute Difference(MAD) value among the candidate SPs. Finally, one of conventional fast search algorithms, such as BRGDS, DS, and three-step search (TSS), has been applied to generate the motion vector of reference block using the final SPs as its starting points. The experimental results showed that the starting points from fine SPs were as dose as to the global minimum as we expected.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.7 no.1
• /
• pp.55-60
• /
• 2014

In this paper, we proposed a method for face region extraction by skin-color hue, saturation and facial feature extraction in natural images. The proposed algorithm is composed of lighting correction and face detection process. In the lighting correction step, performing correction function for a lighting change. The face detection process extracts the area of skin color by calculating Euclidian distances to the input images using as characteristic vectors color and chroma in 20 skin color sample images. Eye detection using C element in the CMY color model and mouth detection using Q element in the YIQ color model for extracted candidate areas. Face area detected based on human face knowledge for extracted candidate areas. When an experiment was conducted with 10 natural images of face as input images, the method showed a face detection rate of 100%.

• The Bulletin of The Korean Astronomical Society
• /
• v.37 no.2
• /
• pp.138.1-138.1
• /
• 2012

자기 구름은 자기 구조를 가지고 방출된 CME로 지구 자기장에 영향을 주는 중요한 원인 중 하나이다. 지구 자기장의 교란으로 발생하는 지자기 활동은 K 지수로 표현되는데 우주기상을 연구하는데 기본 자료로 활용된다. 따라서 자기 구름은 우주기상을 연구하는데 필요한 자료라 할 수 있다. 기존에 Lynch et al.(2005), Huttunen et al.(2005), Lepping et al.(2006), Feng et al.(2007) 등이 만든 자기 구름 리스트가 있지만 자기 구름에 적합하지 않는 이벤트가 적지 않게 포함되어 있어 이벤트를 지자기 활동 연구에 활용하기에 어려움이 있었다. 이 연구에서는 우리만의 자기 구름 기준을 정하고, 이 기준과 실린더 모델을 이용해 새로운 자기 구름 리스트를 완성하였다. 우리가 정한 자기 구름 기준은 (1)자기장의 벡터 성분이 천천히 회전하고 (2)자기장의 세기가 평균보다 세며 (3)자기 구름 지속시간이 7시간보다 짧은 이벤트도 모두 포함하는 것이다. ACE위성과 WIND 위성이 2000년에 관측한 행성간 자기장 자료에 우리의 자기 구름 기준을 적용하여 자기 구름 이벤트 후보를 선정하였고, 마루바시 박사가 만든 실린더 모델을 자기 구름 이벤트 후보에 적용하여 자기 구름 이벤트를 최종 선정하였다. 이렇게 선정된 2000년도 자기 구름 이벤트는 총 63개이고 이를 리스트로 작성하였다. 우리가 만든 자기 구름 이벤트 리스트는 CME와 K 지수 등 지자기 활동 연구에 활용되고 있다.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.9
• /
• pp.2161-2166
• /
• 2015

This paper analyzes the straight line detection using the principal component analysis (PCA) and proposes its improved algorithm to which two new functions are added. The first function removes invalid pixels through the detected straight line and detects a line again. The second function detects lines from non-overlapped blocks, selects valid line candidates, and detects a valid line from pixels adjacent to each line candidate. The proposed algorithm detects a more accurate straight line with a low computation in comparison with the conventional algorithm in an image with somewhat refined lines.

• Journal of Korea Multimedia Society
• /
• v.10 no.5
• /
• pp.559-568
• /
• 2007

Anchor-person scene detection is of significance for video shot semantic parsing and indexing clues extraction in content-based news video indexing and retrieval system. This paper proposes an efficient algorithm extracting anchor ranges that exist in sports news video for unit structuring of sports news. To detect anchor person scenes, first, anchor person candidate scene is decided by DCT coefficients and motion vector information in the MPEG4 compressed video. Then, from the candidate anchor scenes, image processing method is utilized to classify the news video into anchor-person scenes and non-anchor(sports) scenes. The proposed scheme achieves a mean precision and recall of 98% in the anchor-person scenes detection experiment.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.53 no.3
• /
• pp.91-98
• /
• 2016

Detection and classification of underwater objects in sonar imagery are challenging problems. This paper proposes a system that detects and identifies underwater objects at the sea floor level using a sonar image and image processing techniques. The identification process of underwater objects consists of two steps; detection of candidate regions and identification of underwater objects. The candidate regions of underwater objects are extracted by image registration through the detection of common feature points between the reference background image and the current scanning image. And then, underwater objects are identified as the closest pattern within the database using eigenvectors and eigenvalues as features. The proposed system is expected to be used in efficient securement of Q route in vessel navigation.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.47 no.6
• /
• pp.12-18
• /
• 2010

Automatic Target Detection (ATD) systems that use forward-looking infrared (FLIR) consists of three stages. preprocessing, detection, and clutter rejection. All potential targets are extracted in preprocessing and detection stages. But, this results in a high false alarm rates. To reduce false alarm rates of ATD system, true targets are extracted in the clutter rejection stage. This paper focuses on clutter rejection stage. This paper presents a new clutter rejection technique using PCA features and stochastic features of clutters and targets. PCA features are obtained from Euclidian distances using which potential targets are projected to reduced eigenspace selected from target eigenvectors. CV is used for calculating stochastic features of edges in targets and clutters images. To distinguish between target and clutter, LDA (Linear Discriminant Analysis) is applied. The experimental results show that the proposed algorithm accurately classify clutters with a low false rate compared to PCA method or CV method

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.47 no.3
• /
• pp.5-12
• /
• 2010

A novel algorithm which computes the orientations and the locations of mobile robots with repeating feature of ceiling textures is proposed. For orientation computation, the relative angle between a strait line on a ceiling image and the center line of the robot is firstly computed. The relative angle is added to the global reference angles of straight lines of the ceiling and a group of robot orientation candidates is composed. The robot orientation is determined from such orientation candidate group by choosing the closest one to the previous robot orientation. Similarly, the location of the robot is determined from the robot location candidate group by choosing the closest one to the previous robot location, where robot location candidate group is composed by adding the relative location of the robot to global locations of neighboring nodes of the previous robot locations. The experiment has been done to test the accuracy of the algorithm in computing locations and orientations.