• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권5호
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• pp.2348-2365
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• 2018

QR codes as public patent are widely used to acquire the information in various fields. However, it faces security problem when delivering the privacy message by QR code. To overcome this weakness, we propose a secret hiding scheme by improving exploiting modification direction to protect the private message in QR code. The secret messages will be converted into octal digit stream and concealed to the cover QR code by overwriting the cover QR code public message bits. And the private messages can be faithfully decoded using the extraction function. In our secret hiding scheme, the QR code public message still can be fully decoded publicly from the marked QR codes via any standard QR Code reader, which helps to reduce attackers' curiosity. Experiments show that the proposed scheme is feasible, with high secret payload, high security protection level, and resistant to common image post-processing attacks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권3호
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• pp.600-612
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• 2013

In 2006, Zhang and Wang proposed a data hiding scheme based on Exploiting Modification Direction (EMD) to increase data hiding capacity. The major benefit of EMD is providing embedding capacity greater than 1 bit per pixel. Since then, many EMD-type data hiding schemes have been proposed. However, a serious disadvantage common to these approaches is that the embedded data is compromised when the embedding function is disclosed. Our proposed secure data hiding scheme remedies this disclosure shortcoming by employing an additional modulus function. The provided security analysis of our scheme demonstrates that attackers cannot get the secret information from the stegoimage even if the embedding function is made public. Furthermore, our proposed scheme also gives a simple solution to the overflow/underflow problem and maintains high embedding capacity and good stegoimage quality.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권12호
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• pp.5170-5188
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• 2015

This paper proposes a novel progressive secret image-hiding scheme based on the inpainting technique, the vector quantization technique (VQ) and the exploiting modification direction (EMD) technique. The proposed scheme first divides the secret image into non-overlapping blocks and categorizes the blocks into two groups: complex and smooth. The blocks in the complex group are compressed by VQ with PCA sorted codebook to obtain the VQ index table. Instead of embedding the original secret image, the proposed method progressively embeds the VQ index table into the cover images by using the EMD technique. After the receiver recovers the complex parts of the secret image by decoding the VQ index table from the shadow images, the smooth parts can be reconstructed by using the inpainting technique based on the content of the complex parts. The experimental results demonstrate that the proposed scheme not only has the advantage of progressive data hiding, which involves more shadow images joining to recover the secret image so as to produce a higher quality steganography image, but also can achieve high hiding capacity with acceptable recovered image quality.

• 한국CDE학회논문집
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• 제9권1호
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• pp.51-61
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• 2004

Mechanical parts are often grouped into part families based on the similarity of their shapes, to support efficient manufacturing process planning and design modification. The 2-part sequence papers present similarity assessment techniques to support part family classification for machined parts. These exploit the multiple feature decompositions obtained by the feature recognition method using convex decomposition. Convex decomposition provides a hierarchical volumetric representation of a part, organized in an outside-in hierarchy. It provides local accessibility directions, which supports abstract and qualitative similarity assessment. It is converted to a Form Feature Decomposition (FFD), which represents a part using form features intrinsic to the shape of the part. This supports abstract and qualitative similarity assessment using positive feature volumes.. FFD is converted to Negative Feature Decomposition (NFD), which represents a part as a base component and negative machining features. This supports a detailed, quantitative similarity assessment technique that measures the similarity between machined parts and associated machining processes implied by two parts' NFDs. Features of the NFD are organized into branch groups to capture the NFD hierarchy and feature interrelations. Branch groups of two parts' NFDs are matched to obtain pairs, and then features within each pair of branch groups are compared, exploiting feature type, size, machining direction, and other information relevant to machining processes. This paper, the second one of the two companion papers, describes the similarity assessment method using NFD.

• 한국CDE학회논문집
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• 제9권1호
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• pp.44-50
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• 2004

Mechanical parts are often grouped into part families based on the similarity of their shapes, to support efficient manufacturing process planning and design modification. The 2-part sequence papers present similarity assessment techniques to support part family classification for machined parts. These exploit the multiple feature decompositions obtained by the feature recognition method using convex decomposition. Convex decomposition provides a hierarchical volumetric representation of a part, organized in an outside-in hierarchy. It provides local accessibility directions, which supports abstract and qualitative similarity assessment. It is converted to a Form Feature Decomposition (FFD), which represents a part using form features intrinsic to the shape of the part. This supports abstract and qualitative similarity assessment using positive feature volumes. FFD is converted to Negative Feature Decomposition (NFD), which represents a part as a base component and negative machining features. This supports a detailed, quantitative similarity assessment technique that measures the similarity between machined parts and associated machining processes implied by two parts' NFDs. Features of the NFD are organized into branch groups to capture the NFD hierarchy and feature interrelations. Branch groups of two parts' NFDs are matched to obtain pairs, and then features within each pair of branch groups are compared, exploiting feature type, size, machining direction, and other information relevant to machining processes. This paper, the first one of the two companion papers, describes the similarity assessment methods using convex decomposition and FFD.