Implementation of Plateau Histogram Equalization Technique on Thermal Images

Bhavana, D.; Rajesh, V.; Kumar, Karanam Kishore

doi:10.17485/ijst/2016/v9i32/80562

Cited by 5 publications

(2 citation statements)

References 9 publications

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“…To extract features using the DWT we have to compute the coefficient distribution for the selected mother wavelet of the image. The 2D discrete wavelet transform represents an image as the functions which are shifted and dilated which are and the scaling function as which forms the orthonormal basis for [11]. For example, The DWT of an image x(s, t) is decomposed as with , = , ,B…”

Section: Figure3 Wavelet Transform In Image Processingmentioning

confidence: 99%

Detection of Counterfeit Currency using Discrete Wavelet Transform in MATLAB

Prabakaran*,

Reddy,

Gopi

et al. 2019

IJRTE

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Counterfeit notes are one of the major issue in money transactions. In a growing country like India, it is becoming big problem for the economy. As the advances in printing and scanning technologies are developing, it is very easy for any person to print counterfeit notes with use of latest hardware machines. Identifying counterfeit notes in manual way takes a lot of time and manpower. Hence there is requirement of automation technique using which the counterfeit currency recognition process can be done effectively. Many methods have been proposed and implemented with MATLAB. By using Discrete cosine transform (DCT) algorithm blocks of the image are represented by coefficients of DCT. So, due to the presence of blocking articrafts in DCT, it is a drawback for this method. Hence, We have implemented a counterfeit note detection unit with a different algorithm which uses discrete wavelet transform (DWT) in MATLAB. This paper is another attempt on the same project to give a better solution for counterfeit currency problem.

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Section: Figure3 Wavelet Transform In Image Processingmentioning

confidence: 99%

Detection of Counterfeit Currency using Discrete Wavelet Transform in MATLAB

Prabakaran*,

Reddy,

Gopi

et al. 2019

IJRTE

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“…To classify the signals for a particular application a classification technique will be used [17][18][19][20][21]. In some of the pattern recognition applications it is also observed that a signal de-noising is required depending upon the data acquisition techniques [22][23][24][25]. Transforms are applied to some of the application like MRI and CT images to obtain the enhanced image.…”

Section: Introductionmentioning

confidence: 99%

Copy and Move Detection in Audio Recordings using Dynamic Time Warping Algorithm

Mannepalli*¹,

Krishna²,

Krishna³

et al. 2019

IJITEE

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Copy and move forgery technique is a versatile technique used by criminals to change the evidences unlawfully. This is done by removing or adding the segments of an audio recording from another audio using simple software tools . Nowa-days in courts and forensics lab we use digital audio or speech as proof of evidence. With the advancement in digital software and technology it is made possible to modify the original audio data and tamper with it. In this paper we are using a robust method of copy and move detection using MFCC and Dynamic time warping which is robust against several kinds of regularly used post-processing actions and background noise, which highlights its promising potential of the suggested method as an audio tampering detection tool in various practical forensics applications with help of DTW. The proposed method is giving good outcome in differentiating the original sequences and forged sequences. This is done and implemented in mat lab

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