The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Least significant bit (LSB) matching is a well-known steganographic method, which can embed large payload into cover data with good visual and statistical imperceptibility. However, it disturbs the correlation of adjacent pixels in smooth image regions as it randomly modifies half of the payload pixels by 1. Local binary patterns (LBPs) are first proposed as texture features, and can summarize local...
This paper proposes a novel steganalyzer for detecting one of the most popular steganography, LSB matching (also known as “±1 embedding”). The histogram of difference image (the differences of adjacent pixels), which is usually a generalized Gaussian distribution centered at 0, is exploited for deriving statistical features. We have proved theoretically that the peak-value of the histogram would decrease...
It is well-known that least significant bit (LSB) matching is an excellent steganographic algorithm with advantages of high payload, good visual/statistical imperceptibility and extreme ease of implementation. However, some steganalyzers take advantage of the distortion of one-dimensional histogram of LSB matching and can, to some extent, perceive the covert message. Following Cachin's theory, this...
In this paper, we present an improved method for detecting LSB matching steganography in gray-scale image. Our improvements focus on three aspects: (1) instead of using the amplitude of local extrema of the image's histogram in the previous work, we turn to considering the sum of the amplitude of each point in the histogram; (2) incorporating the calibration (downsample) technique with the current...
In this paper, based on a careful investigation on the calibration (downsample) technique, we improve two detectors for detecting LSB matching: calibrated HCF COM and calibrated adjacency HCF COM. Instead of using the COM (center of mass) of the HCF (histogram characteristic function), we consider the ratio of the histogram's DFT coefficients of the image to the corresponding coefficients of the down-sampled...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.