Earticle

Due to powerful computers and advanced photo-editing software tools the manipulation of images has become an easy task. Confirming the authenticity of images and detecting tampered regions in an image without any knowledge about the image content is an important part of the research field. An effort is made to survey the recent advancements being made in the field of digital image forgery detection and thus passive methods for forgery detection are being presented. Blind or passive methods do not require any explicit former information about the image. In the first part, various image forgery detection techniques are classified and then an overview of passive image authentication is presented and the existing blind forgery detection techniques are reviewed

Due to powerful computers and advanced photo-editing software tools the manipulation of images has become an easy task. Confirming the authenticity of images and detecting tampered regions in an image without any knowledge about the image content is an important part of the research field. An effort is made to survey the recent advancements being made in the field of digital image forgery detection and thus passive methods for forgery detection are being presented. Blind or passive methods do not require any explicit former information about the image. In the first part, various image forgery detection techniques are classified and then an overview of passive image authentication is presented and the existing blind forgery detection techniques are reviewed.

This paper presents a time-based Pitch Determination Algorithm (PDA) for reliable estimation of pitch Period (PP) in speech signal. In proposed method, we use the Dyadic Wavelet Transform (DyWT), which detects the presence of Glottal Closure Instants (GCI) and uses the information to determine the pitch period. And, the proposed method also uses the periodicity property of DyWT to detect unsteady GCI. To evaluate the performance of the proposed methods, that of other PDAs based on DyWT are compared with what this paper proposed. The effectiveness of the proposed method is tested with real speech signals containing a transition between voiced and the unvoiced interval where the energy of voiced signal is unsteady. The result shows that the proposed method provides a good performance in estimating the both the unsteady GCI positions as well as the steady parts.

This paper presents a time-based Pitch Determination Algorithm (PDA) for the reliable estimation of Pitch Period (PP) in speech signals. Based on the Dyadic Wavelet Transform (DyWT) , the proposed PDA detects the presence of Glottal Closure Instants (GCI) and uses the information to determine the pitch period. We also examine the problem of conventional PDAs based on DyWT; their performance is compared with the proposition of this paper. The effectiveness of the proposed method is tested with real speech signals containing a transition between the voiced and the unvoiced interval where the energy of the voiced signal is unsteady. The result shows that the proposed method provides good performance in estimating both the unsteady GCI positions as well as the steady parts.