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RISS 인기검색어
- 검색키워드
- 저자 : Saurabh Agarwal(사우랍 아가왈) (검색결과 4 건)
- 무료
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A bibliometric study of image steganalysis
Saurabh Agarwal(사우랍 아가왈),Ki-Hyun Jung(정기현) 대한전자공학회 2021 대한전자공학회 학술대회 Vol.2021 No.6
Image steganography is performed to hide secret information into the image. Image steganalysis is applied to detect steganography. In this paper, a bibliometric study is carried out for image steganalysis from 2002 to 2020. A web of science database is used for bibliometric study. Image steganalysis articles are available in science citation index expanded, social sciences citation index, and emerging sources citation index on the web of science, where image steganalysis and image steganography analysis keywords are used.
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Digital Image Forensics Using Hybrid Feature Set
Saurabh Agarwal(사우랍 아가왈),Ki-Hyun Jung(정기현) 대한전자공학회 2020 대한전자공학회 학술대회 Vol.2020 No.8
Digital images are suitable representation of information since one image can depict lots of information. The changes in the image can be done easily with advance technology, sometimes these changes are performed with malicious purpose. In this paper, a robust technique for median filtering detection is proposed. The co—occurrences of difference pairs are calculated in spatial and frequency domain. The performance is evaluated on three diverse databases. The SVM classifier with linear kernel is utilized to classify non—filtered and median filtered images. The experimental analysis is performed to show the proposed method is better with various environment.
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Forgery Detection Scheme Using Enhanced Markov Model and LBP Texture Operator in Low Quality Images
Saurabh Agarwal(아가왈 사우랍),Ki-Hyun Jung(정기현) 한국정보보호학회 2021 정보보호학회논문지 Vol.31 No.6
본 논문에서는 저품질 이미지에 적용된 미디언 필터링를 검출하는 기법을 제안하고자 한다. 이러한 미디언 필터링 검출은 이미지 포렌식 기법에 사용되고 있는 것으로 제안된 방법에서는 원본 이미지와 미디언 필터링된 이미지를 구분하기 위하여 공간 영역에서 통계적 특징 정보를 추출하고 확장시킨다. 확장된 특징 정보는 마르코프 모델을 사용하고 강인한 특징 집합을 생성하기 위하여 다중 방향 배열을 사용한다. 제안된 방법에서는 검출 정확도를 높이기 위하여 텍스처 연산자를 사용하고 SVM 분류기를 통하여 분류 모델을 훈련시킨다. 실험 결과에서는 JPEG 압축을 사용한 저품질 이미지에서 제안한 방법의 우수함을 보인다. Image forensic is performed to check image limpidness. In this paper, a robust scheme is discussed to detect median filtering in low quality images. Detection of median filtering assists in overall image forensic. Improved spatial statistical features are extracted from the image to classify pristine and median filtered images. Image array data is rescaled to enhance the spatial statistical information. Features are extracted using Markov model on enhanced spatial statistics. Multiple difference arrays are considered in different directions for robust feature set. Further, texture operator features are combined to increase the detection accuracy and SVM binary classifier is applied to train the classification model. Experimental results are promising for images of low quality JPEG compression.
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A Short Bibliometric Analysis of Image Forgery and Forensics
Saurabh Agarwal(아가왈 사우랍),Ki-Hyun Jung(정기현) 대한전자공학회 2023 대한전자공학회 학술대회 Vol.2023 No.6
Social networking services frequently allow users to share digital images. With todays technology, altering an image is not difficult, and occasionally, malicious intention is used to accomplish these modifications. Deep fake images and videos are also generated using a generative adversarial network. Image forensics is applied to detect image forgery, image manipulations, and deep fake images. In this paper, a bibliometric study is carried out from the year 2005 to August 2022. The bibliometric analysis makes use of the Web of Science database. The ((digital) AND (image AND (forensic OR forgery OR manipulation)) OR (deep fake)) query is used for the bibliometric study. Articles on these keywords are found on the Web of Sciences science citation index expanded, conference proceeding citation index-science, the social sciences citation index, and the emerging sources citation index.
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