Using DCT coefficients flipping for information hiding in still images

2010 ◽  
Author(s):  
Radovan Ridzon ◽  
Tomas Kanocz ◽  
Peter Goc-Matis ◽  
Dusan Levicky
Keyword(s):  
Information Hiding ◽  
Still Images ◽  
Dct Coefficients

CMAC WITH CLUSTERING MEMORY AND ITS APPLICATION TO FACIAL EXPRESSION RECOGNITION

2011 ◽  
Vol 25 (07) ◽  
pp. 1055-1072 ◽  
Author(s):  
YU-YI LIAO ◽  
JZAU-SHENG LIN ◽  
SHEN-CHUAN TAI
Keyword(s):  
Facial Expression ◽  
Facial Expression Recognition ◽  
Recognition Rate ◽  
Recognition System ◽  
Expression Recognition ◽  
Test Image ◽  
Frontal View ◽  
Still Images ◽  
Dct Coefficients ◽  
Block Sizes

In this paper, a facial expression recognition system based on cerebella model articulation controller with a clustering memory (CMAC-CM) is presented. Firstly, the facial expression features were automatically preprocessed and extracted from given still images in the JAFFE database in which the frontal view of faces were contained. Next, a block of lower frequency DCT coefficients was obtained by subtracting a neutral image from a given expression image and rearranged as input vectors to be fed into the CMAC-CM that can rapidly obtain output using nonlinear mapping with a look-up table in training or recognizing phase. Finally, the experimental results have demonstrated recognition rates with various block sizes of coefficients in lower frequency and cluster sizes of weight memory. A mean recognition rate of 92.86% is achieved for the testing images. CMAC-CM takes 0.028 seconds for test image in testing phase.

scholarly journals A Study on Digital Watermarking Techniques

2018 ◽  
Vol 4 (3) ◽  
pp. 5
Author(s):  
Garima Bhargava ◽  
Arun Jhapate
Keyword(s):  
Digital Watermarking ◽  
Copyright Protection ◽  
Information Hiding ◽  
Image Watermarking ◽  
Multimedia Systems ◽  
Research Interest ◽  
Transform Domain ◽  
Still Images ◽  
Audio Video ◽  
Networked Multimedia

Digital watermarking was introduced as a result of rapid advancement of networked multimedia systems. It had been developed to enforce copyright technologies for cover of copyright possession. This technology is first used for still images however recently they need been developed for different multimedia objects like audio, video etc. Watermarking, that belong to the information hiding field, has seen plenty of research interest. There's a lot of work begin conducted in numerous branches in this field. The image watermarking techniques might divide on the idea of domain like spatial domain or transform domain or on the basis of wavelets. The copyright protection, capacity, security, strength etc are a number of the necessary factors that are taken in account whereas the watermarking system is intended. This paper aims to produce a detailed survey of all watermarking techniques specially focuses on image watermarking types and its applications in today’s world.

New Proposals for Data Hiding in Paper Media

2013 ◽  
pp. 258-285
Author(s):  
Kitahiro Kaneda ◽  
Keiichi Iwamura
Keyword(s):  
Data Hiding ◽  
Information Hiding ◽  
Extraction Rate ◽  
New Techniques ◽  
Hiding Capacity ◽  
Still Images ◽  
Additional Information ◽  
The Media ◽  
Digital Watermarks ◽  
Information Hiding Capacity

Digital watermarks provide the capability to insert additional information onto various media such as still images, movies, and audios, by utilizing features of the media content. Several techniques that use content features such as text or images have already been proposed for printed documents. The authors propose two new techniques using a single dot pattern and an Artificial Fiber (AF) pattern in order to address the disadvantages of conventional information hiding technologies for paper media. In this chapter, the authors describe each scheme’s characteristics, and how to improve its robustness. As a result, they have attained greater than 80% extraction rate with an information hiding capacity of 91 Kbits in the case of the single dot pattern, and a 100% extraction rate with color characters as the foreground in the case of using artificial fiber patterns.

Identifying Sport Types and Postures with Complex Background by Fusion of Local Descriptors

2015 ◽  
Vol 29 (02) ◽  
pp. 1550008 ◽  
Author(s):  
Piyanan Panakarn ◽  
Suphakant Phimoltares ◽  
Chidchanok Lursinsap
Keyword(s):  
Still Images ◽  
Region Detection ◽  
Background Elimination ◽  
Complex Image ◽  
Challenging Tasks ◽  
Sport Type ◽  
Dct Coefficients ◽  
Edge Histogram ◽  
Type Classification ◽  
Player Detection

Sport type classification and posture identification based on visual meaning of posture semantic in still images are challenging tasks. The difficulty of these tasks comes from the complex image content consisting of a player's posture, the color and texture of a player's clothes as well as complexity of the background. Player detection is one of the most important tasks in posture identification. For sport type classification without object segmentation, the new set of features, based on 64-bins color histogram, DCT coefficients, and Cb and Cr components, is introduced. To achieve high accuracy, an appropriate feature extraction technique should be also realized. For posture identification, three algorithms, concerning player region detection and suitable features for posture identification, are proposed namely blurred background elimination, irrelevant region elimination, and trimming players region. The DFT coefficients, based on image resizing and slicing techniques, are used as significant features in posture identification. Our proposed features were compared with Edge Histogram and Region-based Shape (EH and RS), two of MPEG-7 descriptors. The experimental results showed that our proposed features yielded better performance with 85.76% of accuracy in sport classification and 86.66% of accuracy in posture identification.

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