Digital Camouflage Images Using Two‐scale Decomposition

Computer Graphics Forum

2015

Self Cite

Hidden images contain one or several concealed foregrounds which can be recognized with the assistance of clues preserved by artists. Experienced artists are trained for years to be skilled enough to find appropriate hidden positions for a given image. However, it is not an easy task for amateurs to quickly find these positions when they try to create satisfactory hidden images. In this paper, we present an interactive framework to suggest the hidden positions and corresponding results. The suggested results generated by our approach are sequenced according to the levels of their recognition difficulties. To this end, we propose a novel approach for assessing the levels of recognition difficulty of the hidden images and a new hidden image synthesis method that takes spatial influence into account to make the foreground harmonious with the local surroundings. During the synthesis stage, we extract the characteristics of the foreground as the clues based on the visual attention model. We validate the effectiveness of our approach by performing two user studies, including the quality of the hidden images and the suggestion accuracy.Keywords: image/video editing, image and video processing, texture synthesis, rendering, novel applications of the GPU, rendering ACM CCS: I.4.9 [Image Processing and Computer Vision]: Applications Supporting InformationAdditional Supporting Information may be found in the online version of this article at the publisher's web site: Data S1. Video S1.

Section: Verification Of Hidden-image Synthesismentioning

confidence: 83%

Section: Hidden-image Synthesismentioning

confidence: 99%

See 1 more Smart Citation

Recognition‐Difficulty‐Aware Hidden Images Based on Clue‐Map

Zhao

Computer Graphics Forum

2015

Self Cite

“…Tong et al [32] proposed a method to generate hidden images by first detecting edge features of a hidden object, and then finding a suitable embedding place in the background scene using an energy optimizing process. Du et al [33] utilized the contour completion property of human perception to generate digital camouflage images. In the above-mentioned techniques, although the hidden objects were less noticeable than the background, they are still recognizable by any observers.…”

Section: Related Workmentioning

confidence: 99%

Hidden message in a deformation-based texture

Mao

et al. 2014

Vis Comput

Self Cite

We present stego-texture, a unique texture synthesis method that allows users to deliver personalized messages with beautiful, decorative textures. Our approach was inspired by the success of recent work generating marbling textures using mathematical functions. We were able to transform an input image or a text message into an intricate texture by combining the seven basic, reversible functions provided in the system. Later, the input image or message could be recovered by reversing the process of these functions. During the design process, the parameters of operations were automatically recorded, encrypted and invisibly embedded into the final pattern to create a stego-texture. In this way, the receiver could extract the hidden message from the stego-texture without the need for extra information from the sender. To ensure that the delivered message is unnoticeably covered by the texture, we propose a new technique for automatically creating a background that is harmonious with the message based on a set of visual perception cues. Electronic supplementary materialThe online version of this article (

“…Tong et al [17] proposed a method to generate hidden images by first detecting edge features of a hidden object, and then finding a suitable embedding place in the background scene using an energy optimizing process. Du et al [18] utilized the contour completion property of human perception to generate digital camouflage images. All the above mentioned techniques aim to hide objects in background images by fooling the human recognition process.…”

Section: Related Workmentioning

confidence: 99%

Stego-Marbling-Texture

Mao

2013 International Conference on Computer-Aided Design and Computer Graphics

Jaffer³

et al. 2013

Self Cite

We present stego-marbling-texture, a new and unique texture design method which allows users to deliver personalized messages with beautiful marbling textures. Our approach is inspired by the success of the recent work on modeling traditional marbling operations as mathematical functions. The encrypter transforms an input image or a text message into an intricate marbling pattern using marbling operations defined as reversible functions, and the decrypter recovers the input image or message through reversing the process of marbling operations. When applying marbling operations, the parameters of operations are automatically recorded, encrypted, and then invisibly embedded into the marbling pattern to create a stego-marbling-texture. In this way, the decrypter can be implemented as a stand along software, enabling the receiver to extract the hidden message from the stego-marbling-texture without requiring any extra information from the sender. To ensure that the message is unnoticeably and beautifully covered by the marbling texture, we propose a new technique for automatically creating a background which is harmonious with the input message based on a set of visual perception cues.