• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권8호
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• pp.4300-4314
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• 2019

With the development of video-related applications, media content has increased dramatically through applications. There is a substantial amount of near-duplicate videos (NDVs) among Internet videos, thus NDVR is important for eliminating near-duplicates from web video searches. This paper proposes a novel NDVR system that supports large-scale retrieval and contributes to the efficient and accurate retrieval performance. For this, we extracted keyframes from each video at regular intervals and then extracted both commonly used features (LBP and HSV) and new image features from each keyframe. A recent study introduced a new image feature that can provide more robust information than existing features even if there are geometric changes to and complex editing of images. We convert a vector set that consists of the extracted features to binary code through a set of hash functions so that the similarity comparison can be more efficient as similar videos are more likely to map into the same buckets. Lastly, we calculate similarity to search for NDVs; we examine the effectiveness of the NDVR system and compare this against previous NDVR systems using the public video collections CC_WEB_VIDEO. The proposed NDVR system's performance is very promising compared to previous NDVR systems.

• 방송공학회논문지
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• 제20권4호
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• pp.641-644
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• 2015

본 논문에서는 이진 프레임 기술자와 이를 이용한 프레임 단위 유사중복 동영상 정합 알고리즘을 제안한다. 우선 동영상으로부터 취득한 프레임을 패치(patch)단위로 나누고 패치간의 관계를 이진으로 나타낸다. 그리고 두 동영상 프레임 간의 정합비용과 보상비용으로 비용 함수를 표현한다. 초기 정합과 반복적인 정합 갱신을 통해 비용 함수를 최소화한다. 실험을 통해 제안하는 이진 프레임 기술자의 적합성과 프레임 단위 정합 알고리즘 성능이 우수함을 확인한다.

• 전기학회논문지
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• 제67권10호
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• pp.1358-1363
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• 2018

As the usage of the Internet grows and digital media become more diversified, it has become much easier for digital contents to be distributed and shared. This makes easier to access the desired digital contents. On the other hand, there is an increasing need to protect the copyright of digital works. There are some prevalent ways to protect ownership, but they accompany several disadvantages. Among those ways, watermarking methods have the advantage of ensuring invisibility, but they also have a disadvantage that they are vulnerable to external attacks such as a noise and signal processing. In this paper, we propose the detecting method of illegal contents that is robust against external attacks to protect digital works. We extract HSV and LBP features from images and use Euclidian-based hashing techniques to shorten the searching time on high-dimensional and near-duplicate videos. According to the results, the proposed method showed higher detection rates than that of the Watermarking techniques in terms of the images with fabrications or deformations.