Ching-Nung Yang

Effective and Efficient Global Context Verification for Image Copy Detection

To detect illegal copies of copyrighted images, recent copy detection methods mostly rely on the bag-of-visual-words (BOW) model, in which local features are quantized into visual words for image matching. However, both the limited discriminability of local features and the BOW quantization errors will lead to many false local matches, which make it hard to distinguish similar images from copies. Geometric consistency verification is a popular technology for reducing the false matches, but it neglects global context information of local features and thus cannot solve this problem well. To address this problem, this paper proposes a global context verification scheme to filter false matches for copy detection. More specifically, after obtaining initial scale invariant feature transform (SIFT) matches between images based on the BOW quantization, the overlapping region-based global context descriptor (OR-GCD) is proposed for the verification of these matches to filter false matches. The OR-GCD not only encodes relatively rich global context information of SIFT features but also has good robustness and efficiency. Thus, it allows an effective and efficient verification. Furthermore, a fast image similarity measurement based on random verification is proposed to efficiently implement copy detection. In addition, we also extend the proposed method for partial-duplicate image detection. Extensive experiments demonstrate that our method achieves higher accuracy than the state-of-the-art methods, and has comparable efficiency to the baseline method based on the BOW quantization.

Improvements of image sharing with steganography and authentication

Recently, Lin and Tsai proposed an image secret sharing scheme with steganography and authentication to prevent participants from the incidental or intentional provision of a false stego-image (an image containing the hidden secret image). However, dishonest participants can easily manipulate the stego-image for successful authentication but cannot recover the secret image, i.e., compromise the steganography. In this paper, we present a scheme to improve authentication ability that prevents dishonest participants from cheating. The proposed scheme also defines the arrangement of embedded bits to improve the quality of stego-image. Furthermore, by means of the Galois Field GF(2^8), we improve the scheme to a lossless version without additional pixels.

New Colored Visual Secret Sharing Schemes

Visual secretsharing (VSS) schemes are used to protect the visual secret bysending n transparencies to different participantsso that k-1 or fewer of them have no informationabout the original image, but the image can be seen by stackingk or more transparencies. However, the revealedsecret image of a conventional VSS scheme is just black and white.The colored k out of n VSS scheme sharinga colored image is first introduced by Verheul and Van Tilborg[1]. In this paper, a new construction for the colored VSS schemeis proposed. This scheme can be easily implemented on basis ofa black & white VSS scheme and get much better block lengththan the Verheul-Van Tilborg scheme.

Enabling Semantic Search based on Conceptual Graphs over Encrypted Outsourced Data

Currently, searchable encryption is a hot topic in the field of cloud computing. The existing achievements are mainly focused on keyword-based search schemes, and almost all of them depend on predefined keywords extracted in the phases of index construction and query. However, keyword-based search schemes ignore the semantic representation information of users’ retrieval and cannot completely match users’ search intention. Therefore, how to design a content-based search scheme and make semantic search more effective and context-aware is a difficult challenge. In this paper, for the first time, we define and solve the problems of semantic search based on conceptual graphs (CGs) over encrypted outsourced data in clouding computing (SSCG). We first employ the efficient measure of “sentence scoring” in text summarization and Tregex to extract the most important and simplified topic sentences from documents. We then convert these simplified sentences into CGs. To perform quantitative calculation of CGs, we design a new method that can map CGs to vectors. Next, we rank the returned results based on “text summarization score”. Furthermore, we propose a basic idea for SSCG and give a significantly improved scheme to satisfy the security guarantee of searchable symmetric encryption (SSE). Finally, we choose a real-world dataset, i.e., the CNN dataset to test our scheme. The results obtained from the experiment show the effectiveness of our proposed scheme.

Aspect ratio invariant visual secret sharing schemes with minimum pixel expansion

Visual secret sharing (VSS) scheme is a perfect secure method to hide a secret image by breaking it into shadow images and one can decode it easily by the human visual system. We use m, the pixel expansion, subpixels to represent a pixel. Suppose the secret image is a circle and m is not a square value, i.e., the aspect ratio is changed. After performing the VSS technique, the circle will be changed to an ellipse and consequently lead to the loss of information. To avoid distorting the image, the dummy subpixels are added to keep the aspect ratio unchanged. In this paper, we propose a novel method to dramatically reduce the number of extra subpixels to construct the aspect ratio invariant VSS schemes.

Colored visual cryptography scheme based on additive color mixing

A (t,n) visual cryptography scheme (VCS) encodes a secret image into n shadow images (shadows) distributed among n participants. When any qualified set of at least t participants stack their shadows, the secret image can be visually revealed. The first VCS proposed by Naor and Shamir was only designed for encrypting a black-and-white secret image; subsequently, some colored VCSs (CVCSs) for sharing colored images were proposed to enhance the applicability. In CVCSs, we usually use several color subpixels to represent a secret pixel where the number of subpixels is referred to as the pixel expansion. Generally, the CVCS requires a larger pixel expansion to produce more colors; however, this expansion will increase the shadow size. We therefore study the additive color mixing in a probabilistic way and propose a new CVCS whose pixel expansion is fixed and improves on the previous CVCSs, at the price of reducing the contrast quality to certain level.

Image secret sharing method with two-decoding-options: Lossless recovery and previewing capability

Visual cryptography scheme (VCS) is a research area in image secret sharing, where one can easily stack shadow images and decode a black-and-white secret image through the human visual system without computation. Although VCS does not provide a competitive reconstruction quality, its stacking-to-see property clearly has the intended applications. To develop the ease of decoding of VCS and simultaneously overcome its weakness, Lin et al. recently proposed a novel two-in-one image secret sharing scheme (TiOISSS) with two decoding options based on VCS and a polynomial-based image secret sharing scheme (PISSS). In this TiOISSS, the first decoding stage has the stacking-to-see property to preview a vague image, and the second decoding stage is to obtain the original gray-level secret image. In this paper, we design a new TiOISSS by combining VCS and PISSS in a different way; in specific, our new scheme reduce shadow image size, and is more suitable for faster transmission within a distributed multimedia system.

Improvements of a two-in-one image secret sharing scheme based on gray mixing model

Yang and Ciou recently proposed a two-in-one image secret sharing scheme (TiOISSS), which can easily preview a vague image by human eyes, but also provide a perfect reconstruction of the original image by computation. However, their scheme cannot recover the lossless image by computation as they claimed. In this paper, we resolve the problem of lossless reconstruction. In addition, we improve the visual quality of the previewed image. Also, we introduce a new definition of contrast to evaluate the visual quality of the previewed image. Compared with Yang and Cious TiOISSS, our scheme can gain the lossless secret image and meantime enhance the contrast of previewed image.

EXTENDED VISUAL SECRET SHARING SCHEMES: IMPROVING THE SHADOW IMAGE QUALITY

Visual secret sharing (VSS) scheme is a perfectly secure method to divide a secret image into several noise-like shadow images by splitting a secret pixel into black and white subpixels. Unlike other secret sharing schemes, the VSS scheme can be easily decoded by the human visual sight when staking shadow images. However, noise-like shadows are unusual and suspected by censors when delivered by e-mail or fax. Also, noise-like shadows are difficult to identify and manage when distributed. The problem was solved by adding the extended capability, a meaningful shadow image, in the so-called extended visual secret sharing (EVSS) scheme. In this paper, we present a new EVSS scheme by using gray and white subpixels to represent the secret pixel. Our proposed scheme still has the capability of visually revealing the secret image by stacking shadow images without the help of hardware and complex computation. When compared to the previous EVSS scheme, our new scheme has less number of subpixels to represent a secret pixel and the clearer shadow images.

Reduce shadow size in aspect ratio invariant visual secret sharing schemes using a square block-wise operation

An aspect ratio invariant visual secret sharing (ARIVSS) scheme is a perfectly secure method for sharing secret images. Due to the nature of the VSS encryption, each secret pixel is expanded to m sub-pixels in each of the generated shares. The advantage of ARIVSS is that the aspect ratio of the recovered secret image is fixed and thus there is no loss of information when the shape of the secret image is our information. For example, a secret image of a circle is compromised to an ellipse if m does not have a square value. Two ARIVSS schemes based on processing one and four pixel blocks, respectively, were previously proposed. In this paper, we have generalized the square block-wise approach to further reduce pixel expansion.