Results 241 to 250 of about 88,813 (284)

Adaptive Histogram Shifting Based Reversible Data Hiding

2017
Reversible data hiding (RDH) is a special kind of data hiding technique which can exactly recover the cover image from the stego image after extracting the hidden data. Recently, Wu et al. proposed a novel RDH method with contrast enhancement (RDH-CE).
Yonggwon Ri, Jing Dong, Wei Wang, Tieniu Tan   +3 more
openaire   +1 more source

Three-dimensional histogram shifting for reversible data hiding

Multimedia Systems, 2016
Histogram shifting is an important method of reversible data hiding. However, every pixel, difference, or prediction-error is respectively changed to hide a data bit in the traditional histogram shifting, which constrains the capacity-distortion embedding performance.
Juan Zhao, Zhitang Li
openaire   +1 more source

On Fitting Polynomials to Averaged Shifted Histograms

GSTF Journal of Mathematics, Statistics and Operations Research, 2014
This paper proposes univariate and bivariate density estimation techniques whereby averaged shifted histograms are smoothed by means of polynomials. In the univariate case, the density estimate is obtained as a moment-based polynomial approximation to an averaged shifted histogram.
openaire   +1 more source

Improved reversible data hiding using histogram shifting method

2015 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES), 2015
A reversible data hiding (RDH) algorithm with improved security, which can reacquire the cover in separable manner from the marked stego-image is presented in this paper. In the content owner side cover image is encrypted by deploying user-defined security key derived-chaotic based transposition algorithm.
Arun K Mohan, M R Saranya, K Anusudha
openaire   +1 more source

Reversible watermarking based on interpolation error histogram shifting

2010 5th International Symposium on Telecommunications, 2010
A reversible data hiding technique with high capacity of data embedding is presented in this paper. Using both difference expansion and histogram shifting methods at the same time we have improved Luo et al.'s method to increase the amount of data that can be embedded into the host image.
M.A.M. Abadi, Habibollah Danyali, Mohammad Sadegh Helfroush   +2 more
openaire   +1 more source

Mean Shift Tracking with Advanced Background-Weighted Histogram

Applied Mechanics and Materials, 2013
Tracking objects in videos using mean shift technique has brought to public attention. In background-weighted histogram (BWH) algorithm proposed by Kernel-Based Object tracking attempts to reduce the interference of background target localization in mean shift tracking.
Abebe Yirga Alemu, Zhi Jun Pei, Jun Zhang   +2 more
openaire   +1 more source

Improved Histogram-Shifting-Imitated Reversible Data Hiding Scheme

2015 12th International Conference on Information Technology - New Generations, 2015
Wang et al. proposed a histogram shifting imitation based reversible data hiding scheme in 2013. They used the peak points of image intensity-based segments, instead of utilizing the peak point of an histogram. Their scheme has the limitation of the embedding capacity due to the embedding method. In this paper, we propose an improved data hiding scheme
Pyung-Han Kim, Dae-Soo Kim, Kee-Young Yoo   +2 more
openaire   +1 more source

A Reversible Watermarking Based on Histogram Shifting

2006
In this paper, we propose a reversible watermarking algorithm where an original image can be recovered from watermarked image data. Most watermarking algorithms cause degradation of image quality in original digital content in the process of embedding watermark.
JinHa Hwang, JongWeon Kim, JongUk Choi
openaire   +1 more source

Mean-shift video tracking using color-LSN histogram

2010 5th International Symposium on Telecommunications, 2010
A texture based object tracking algorithm is presented. The algorithm is an extension to famous mean-shift tracking method. It does not rely on color histogram. It incorporates both color histogram and texture histogram information to model tracking target.
Hamed Rezazadegan Tavakoli, M. Shahram Moin   +1 more
openaire   +1 more source

Mean Shift tracking with multiple reference color histograms

Computer Vision and Image Understanding, 2010
The Mean Shift tracker is a widely used tool for robustly and quickly tracking the location of an object in an image sequence using the object's color histogram. The reference histogram is typically set to that in the target region in the frame where the tracking is initiated.
Ido Leichter, Michael Lindenbaum, Ehud Rivlin   +2 more
openaire   +1 more source