کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
383019 660800 2013 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Color local complexity estimation based steganographic (CLCES) method
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Color local complexity estimation based steganographic (CLCES) method
چکیده انگلیسی

In this paper we present the color local complexity estimation based steganographic (CLCES) method that is able of both preventing visual degradation and providing a large embedding capacity. A preprocessing stage is applied in the proposed scheme to improve the steganography security. The embedding capacity of each pixel is determined by the local complexity of the cover image, allowing good visual quality as well as embedding a large amount of secret messages. We classify the pixels using a threshold based on the standard deviation of the local complexity in the cover image to provide a compromise between the embedding capacity and the image visual quality. The experimental results demonstrated that the algorithm CLCES proposed produces insignificant visual distortion due to the hidden message. It provides a high embedding capacity that is superior respect to the offered by the existing schemes. The proposed method is a secure steganographic algorithm; it can resist the image quality measures (IQM) steganalysis attack. The RGB, YCbCr, and HSV color spaces are incorporated in the proposed scheme to ensure that the difference between the cover image and the stego-image which is indistinguishable by the human visual system (HVS). Finally, the proposed scheme is simple, efficient, and feasible for the adaptive steganographic applications.


► The method is able to prevent visual degradation and provide large embedding capacity.
► The method is secure steganographic algorithm resisting the IQM steganalysis attack.
► Color spaces are incorporated to be indistinguishable by the human visual system.
► The scheme is simple, efficient, and feasible for steganographic applications.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 40, Issue 4, March 2013, Pages 1132–1142
نویسندگان
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