• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.579-582
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• 2019

이미지의 특정 객체를 제거할 때, 주변 환경을 고려하면서 제거하기에 어려움이 있다. 본 연구는 특정 객체가 제거되면서 생기는 빈자리를 자연스럽게 보완하기 위해서 이미지 내용을 기반으로 이미지를 변경하는 Seam Carving 알고리즘을 이용하여 보다 자연스러운 결과 이미지를 생성하는 프로그램을 구현했다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.80-89
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• 2011

In this paper, a new real time video scaling technique which preserved the contents of a movie was proposed. Because in a movie a correlation exists between consecutive frames, in this paper by determining the seam of the current frame considering the seam of the previous frame, it was proposed the real time video scaling technique without the shaking phenomenon of the contents even though the entire video is not analyzed. For this purpose, frames which have similar features in a movie are classified into a scene, and the first frame of a scene is resized by the seam carving at the static images so that it can preserve the contents of the image to the utmost. At this time, the information about the seam extracted to convert the image size is saved, and the sizes of the next frames are controlled with reference to the seam information stored in the previous frame by each frame. The proposed algorithm has the fast processing speed of the extent of being similar to a bilinear method and preserves the main content of an image to the utmost at the same time. Also because the memory usage is remarkably small compared with the existing seam carving method, the proposed algorithm is usable in the mobile terminal in which there are many memory restrictions. Computer simulation results indicate that the proposed technique provides better objective performance and subjective image quality about the real time processing and shaking phenomenon removal and contents conservation than conventional algorithms.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.77-86
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• 2013

In this paper, we propose a fast video retargeting method which preserves the contents of a video and converts the image size. Since the conventional Seam Carving which is the well-known content-aware image retargeting technique uses the dynamic programming method, the repetitive update procedure of the accumulation energy is absolutely needed to obtain seam. The energy update procedure cannot avoid the processing time delay because of many operations by the image full-searching. By applying the proposed method, frames which have similar features in video are classified into a scene, and the first frame of a scene is resized by the modified Seam Carving where multiple seams are extracted from candidate seams to reduce the repetitive update procedure. After resizing the first frame of a scene, all continuous frames of the same scene are resized with reference to the seam information stored in the previous frame without the calculation of the accumulation energy. Therefore, although the fast processing is possible with reducing complexity and without analyzing all frames of scene, the quality of an image can be analogously maintained with an existing method. The experimental results show that the proposed method can preserve the contents of an image and can be practically applied to retarget the image on real time.