In this paper, we present a novel text line segmentation framework following the divide-and-conquer paradigm:
we iteratively identify and re-process regions of ambiguous line segmentation from an input document image
until there is no ambiguity. To detect ambiguous line segmentation, we introduce the use of two complimentary
line descriptors, referred as to the underline and highlight line descriptors, and identify ambiguities when their
patterns mismatch. As a result, we can easily identify already good line segmentations, and largely simplify the
original line segmentation problem by only reprocessing ambiguous regions. We evaluate the performance of the
proposed line segmentation framework using the ICDAR 2009 handwritten document dataset, and it is close to
top-performing systems submitted to the competition. Moreover, the proposed method is also robust against
skewness, noise, variable line heights and touching characters. The proposed idea can also be applied to other
text analysis tasks such as word segmentation and page layout analysis.
This paper discusses the problem of testing the degree of randomness within an image, particularly for a shuffled or encrypted image. Its key contributions are: 1) a mathematical model of perfectly shuffled images; 2) the derivation of the theoretical distribution of pixel differences; 3) new hypothesis tests based approach to differentiate whether or not a test image is perfectly shuffled; and 4) a randomized algorithm to unbiasedly evaluate the degree of image randomness. Simulation results show that the proposed method is robust and effective in evaluating the degree of image randomness, and may often be more suitable for image applications than commonly used testing schemes designed for binary data like NIST 800-22 test suites. The developed method may be also useful as a first step to determine whether or not an image shuffling or encryption scheme is suitable for a particular cryptographic application.
Chaos maps and chaotic systems have been proved to be useful and effective for cryptography. In our study, the two-dimensional logistic map with complicated basin structures and attractors are first used for image encryption. The proposed method adopts the classic framework of the permutation-substitution network in cryptography and thus ensures both confusion and diffusion properties for a secure cipher. The proposed method is able to encrypt an intelligible image into a random-like one from the statistical point of view and the human visual system point of view. Extensive simulation results using test images from the USC-SIPI image database demonstrate the effectiveness and robustness of the proposed method. Security analysis results of using both the conventional and the most recent tests show that the encryption quality of the proposed method reaches or excels the current state-of-the-art methods. Similar encryption ideas can be applied to digital data in other formats (e.g., digital audio and video). We also publish the cipher MATLAB open-source-code under the web page https://sites.google.com/site/tuftsyuewu/source-code.
This paper introduces a new effective and lossless image encryption algorithm using a Sudoku Matrix to scramble and
encrypt the image. The new algorithm encrypts an image through a three stage process. In the first stage, a reference
Sudoku matrix is generated as the foundation for the encryption and scrambling processes. The image pixels' intensities
are then changed by using the reference Sudoku matrix values, and then the pixels' positions are shuffled using the
Sudoku matrix as a mapping process. The advantages of this method is useful for efficiently encrypting a variety of
digital images, such as binary images, gray images, and RGB images without any quality loss. The security keys of the
presented algorithm are the combination of the parameters in a 1D chaotic logistic map, a parameter to control the size of
Sudoku Matrix and the number of iteration times desired for scrambling. The possible security key space is extremely
large. The principles of the presented scheme could be applied to provide security for a variety of systems including
image, audio and video systems.
Conference Committee Involvement (6)
Mobile Multimedia/Image Processing, Security, and Applications 2018
16 April 2018 | Orlando, FL, United States
Mobile Multimedia/Image Processing, Security, and Applications 2017
10 April 2017 | Anaheim, CA, United States
Mobile Multimedia/Image Processing, Security, and Applications 2016
18 April 2016 | Baltimore, MD, United States
Mobile Multimedia/Image Processing, Security, and Applications 2015
20 April 2015 | Baltimore, MD, United States
Mobile Multimedia/Image Processing, Security, and Applications 2014
5 May 2014 | Baltimore, MD, United States
Mobile Multimedia/Image Processing, Security, and Applications 2013
29 April 2013 | Baltimore, Maryland, United States
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