scholarly journals Discrete wavelet transform processing system based on digital watermarking algorithm

2021 ◽  
Vol 2083 (4) ◽  
pp. 042075
Author(s):  
Miao Shi
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Digital Watermarking ◽  
Basic Principle ◽  
Low Frequency ◽  
Processing System ◽  
Discrete Wavelet ◽  
Noise Interference ◽  
Arnold Scrambling

Abstract This paper introduces the concept of multimedia digital watermarking and summarizes the current technology status. This paper summarizes the research status and basic principle of digital watermarking. The advantages of digital watermarking algorithm based on wavelet transform are analyzed. The proposed algorithm combines Arnold scrambling method and DWT transform multi-resolution characteristics, and adopts linear and different embedding strength methods. Effectively improve the security of the watermark. According to the classification results, different intensity watermarking components are embedded into the DCT low frequency coefficients of different image blocks. Experimental results show that this algorithm has strong masking and robustness, and the watermarking realized by using the proposed algorithm has good robustness against common image processing and noise interference.

A Kind of DWT Domain Image Digital Watermarking Algorithm Research

2014 ◽  
Vol 1044-1045 ◽  
pp. 991-994
Author(s):  
Tao Liu
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Frequency Domain ◽  
Digital Watermarking ◽  
Wavelet Decomposition ◽  
Low Frequency ◽  
Discrete Wavelet ◽  
Original Image ◽  
Adaptive Watermarking ◽  
Frequency Domain Methods

An image-adaptive watermarking algorithm based on wavelet transform was proposed. At first, A digital image used as watermarking was scrambled. Next, the original image was decomposed by discrete wavelet transform,and in accordance with the characteristics of human visual system, wavelet decomposition in the low-frequency domain, Methods which average of adjacent domain instead of single wavelet decomposition coefficients was used to estimate and quantitative, watermarking was adaptively embedded in wavelet coefficients of low-frequency domain. At last, the simulation experimental results show that the algorithm for a variety of conventional image processing has good robustness.

SOME NOTES ON THE APPLICATION OF DISCRETE WAVELET TRANSFORM IN IMAGE PROCESSING

2011 ◽  
Author(s):  
Egydio C. S. Caria ◽  
Trajano A. de A. Costa ◽  
João Marcos A. Rebello ◽  
Donald O. Thompson ◽  
Dale E. Chimenti
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet

scholarly journals Multi-focus Image Fusion Using an Effective Discrete Wavelet Transform Based Algorithm

2014 ◽  
Vol 14 (2) ◽  
pp. 102-108 ◽  
Author(s):  
Yong Yang ◽  
Shuying Huang ◽  
Junfeng Gao ◽  
Zhongsheng Qian
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
Discrete Wavelet Transform ◽  
High Frequency ◽  
Low Frequency ◽  
Objective Evaluation ◽  
Discrete Wavelet ◽  
Evaluation Indexes ◽  
Fused Image ◽  
Focus Image

Abstract In this paper, by considering the main objective of multi-focus image fusion and the physical meaning of wavelet coefficients, a discrete wavelet transform (DWT) based fusion technique with a novel coefficients selection algorithm is presented. After the source images are decomposed by DWT, two different window-based fusion rules are separately employed to combine the low frequency and high frequency coefficients. In the method, the coefficients in the low frequency domain with maximum sharpness focus measure are selected as coefficients of the fused image, and a maximum neighboring energy based fusion scheme is proposed to select high frequency sub-bands coefficients. In order to guarantee the homogeneity of the resultant fused image, a consistency verification procedure is applied to the combined coefficients. The performance assessment of the proposed method was conducted in both synthetic and real multi-focus images. Experimental results demonstrate that the proposed method can achieve better visual quality and objective evaluation indexes than several existing fusion methods, thus being an effective multi-focus image fusion method.

scholarly journals HOUGH TRANSFORM GENERATED STRONG IMAGE HASHING SCHEME FOR COPY DETECTION

2018 ◽  
Author(s):  
Mayank Srivastava ◽  
Jamshed M Siddiqui ◽  
Mohammad Athar Ali
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Hough Transform ◽  
Rapid Development ◽  
Discrimination Performance ◽  
Discrete Wavelet ◽  
Image Hashing ◽  
Copy Detection ◽  
Detection Scheme

The rapid development of image editing software has resulted in widespread unauthorized duplication of original images. This has given rise to the need to develop robust image hashing technique which can easily identify duplicate copies of the original images apart from differentiating it from different images. In this paper, we have proposed an image hashing technique based on discrete wavelet transform and Hough transform, which is robust to large number of image processing attacks including shifting and shearing. The input image is initially pre-processed to remove any kind of minor effects. Discrete wavelet transform is then applied to the pre-processed image to produce different wavelet coefficients from which different edges are detected by using a canny edge detector. Hough transform is finally applied to the edge-detected image to generate an image hash which is used for image identification. Different experiments were conducted to show that the proposed hashing technique has better robustness and discrimination performance as compared to the state-of-the-art techniques. Normalized average mean value difference is also calculated to show the performance of the proposed technique towards various image processing attacks. The proposed copy detection scheme can perform copy detection over large databases and can be considered to be a prototype for developing online real-time copy detection system.   

Real-Time Vehicle License Plate Recognition Based on Scanning and 2D Haar Discrete Wavelet Transform

2013 ◽  
Vol 284-287 ◽  
pp. 2402-2406 ◽  
Author(s):  
Rong Choi Lee ◽  
King Chu Hung ◽  
Huan Sheng Wang
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Real Time ◽  
Recognition Rate ◽  
Low Frequency ◽  
Experimental Result ◽  
Discrete Wavelet ◽  
License Plate ◽  
License Plate Recognition ◽  
Image Pixels

This thesis is to approach license-plate recognition using 2D Haar Discrete Wavelet Transform (HDWT) and artificial neural network. This thesis consists of three main parts. The first part is to locate and extract the license-plate. The second part is to train the license-plate. The third part is to real time scan recognition. We select only after the second 2D Haar Discrete Wavelet Transform the image of low-frequency part, image pixels into one-sixteen, thus, reducing the image pixels and can increase rapid implementation of recognition and the computer memory. This method is to scan for car license plate recognition, without make recognition of the individual characters. The experimental result can be high recognition rate.

A Content-Based Watermarking Scheme for Image Authentication Using Discrete Wavelet Transform Inter-Coefficient Relations

2011 ◽  
pp. 173-187
Author(s):  
Latha Parameswaran ◽  
K Anbumani
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Image Authentication ◽  
Binary String ◽  
Discrete Wavelet ◽  
Host Image ◽  
Relationship Of ◽  
Watermarking Scheme ◽  
Authentication Technique

This chapter discusses a content-based authentication technique based on inter-coefficient relationship of Discrete Wavelet Transform (DWT). Watermark is generated from the first level DWT. An image digest (which is a binary string) is generated from the second level DWT. The watermark is embedded in the mid-frequency coefficients of first level DWT as directed by the image digest. Image authentication is done by computing the Completeness of Signature. The proposed scheme is capable of withstanding incidental image processing operations such as compression and identifies any malicious tampering done on the host image.

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