Audio Fragment Identification System

Jin, Xun; Kim, Jongweon

doi:10.14257/ijmue.2014.9.12.28

Cited by 2 publications

(3 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is difficult to achieve high precision of format classification only using statistical features, because all the video files involve high entropy coding. In this paper, we use a combination of statistical and structural features as the format feature as described in [19]. In [19], it was used as audio format feature, however in this paper, we apply it to the video approach.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we use a combination of statistical and structural features as the format feature as described in [19]. In [19], it was used as audio format feature, however in this paper, we apply it to the video approach. The format classifier uses a kind of subspace clustering method, called discriminative subspace clustering as described in [20].The well-known K-nearest neighbor is employed in the procedure of format identification.…”

Section: Introductionmentioning

confidence: 99%

“…Because of losing the important meta-information, most fragments fail to be extracted the inside content. Therefore, we utilize a method of fragment recovery to recover the video content as in [19]. We collect numerous file headers from video samples and form a group of headers in advance.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Practical Video Fragment Identification System

Jin¹,

Kim²

2015

IJMUE

Self Cite

View full text Add to dashboard Cite

In this paper, we present a practical identification approach of video fragment for digital video files. Before analyzing the video content, we must decode it based on its encoding format first. In order to effectively identify the format of a fragment, a format classification is performed before the format identification. The methods of format classification and identification are discriminative subspace clustering (DiSC) and the Knearest neighbor (KNN).Because of losing the meta-information, we add a maximum similar header (MSH) to the front of the fragment to recover the video content. We adopt a simple key frame detection method using standard deviation and mean value. Motion vectors of macro blocks are utilized to classify the video features for effectively identifying the video. Several edges of frames are accumulated and compose a video feature. The experimental results show the evaluations of the video format classification and identification, fragment recovery, and content identification.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Practical Video Fragment Identification System

Jin¹,

Kim²

2015

IJMUE

Self Cite

View full text Add to dashboard Cite

show abstract

Fragments‐Expert: A graphical user interface MATLAB toolbox for classification of file fragments

Teimouri

Seyedghorban

Amirjani

2020

Concurrency and Computation

View full text Add to dashboard Cite

Summary The classification of file fragments of various file formats is an essential task in various applications such as firewalls, intrusion detection systems, antiviruses, web content filtering, and digital forensics. However, the community lacks a suitable software tool that can integrate major methods for feature extraction from file fragments and classification among various file formats. In this article, we present Fragments‐Expert that is a graphical user interface MATLAB toolbox for the classification of file fragments. It provides users with 23 categories of features extracted from file fragments. These features can be employed by seven categories of machine learning algorithms for the task of classification among various file formats.

show abstract

Audio Fragment Identification System

Abstract: Abstract

Cited by 2 publications

References 20 publications

A Practical Video Fragment Identification System

A Practical Video Fragment Identification System

Fragments‐Expert: A graphical user interface MATLAB toolbox for classification of file fragments

Contact Info

Product

Resources

About