Reversible Information of Encrypted Image Based on Feature Difference Detection and Wavelet Transform

Aiming at the shortcomings of the existing lossless digital watermarking algorithm based on frequency domain in reversibility and embedding capacity, this study proposes a lossless digital image watermarking algorithm based on fractional wavelet transform, which is used for large-capacity reversible information hiding of images. First, the image is transformed by LeGall5/3 fractional wavelet, and then, the watermark is embedded in the high-frequency subband by the histogram shift method. In order to obtain maximum embedding capacity and reduce image distortion, the methods of selecting embedding parameters and stopping parameters are proposed, respectively. At the same time, in order to prevent overflow and reduce additional information, a new method of generating position map is proposed. The experimental results show that Lena is the result of multilayer embedding based on the algorithm in this study. In order to better observe the distortion phenomenon and enlarge the image, the Lena test image is the watermark image obtained after two and three layers of embedding, and its embedding capacity can be 2.7 bpp. It is proved that wavelet transform is suitable for encrypted images to implement covert communication.

Virtual Namesake Point Multi-Source Point Cloud Data Fusion Based on FPFH Feature Difference

There are many sources of point cloud data, such as the point cloud model obtained after a bundle adjustment of aerial images, the point cloud acquired by scanning a vehicle-borne light detection and ranging (LiDAR), the point cloud acquired by terrestrial laser scanning, etc. Different sensors use different processing methods. They have their own advantages and disadvantages in terms of accuracy, range and point cloud magnitude. Point cloud fusion can combine the advantages of each point cloud to generate a point cloud with higher accuracy. Following the classic Iterative Closest Point (ICP), a virtual namesake point multi-source point cloud data fusion based on Fast Point Feature Histograms (FPFH) feature difference is proposed. For the multi-source point cloud with noise, different sampling resolution and local distortion, it can acquire better registration effect and improve the accuracy of low precision point cloud. To find the corresponding point pairs in the ICP algorithm, we use the FPFH feature difference, which can combine surrounding neighborhood information and have strong robustness to noise, to generate virtual points with the same name to obtain corresponding point pairs for registration. Specifically, through the establishment of voxels, according to the F2 distance of the FPFH of the target point cloud and the source point cloud, the convolutional neural network is used to output a virtual and more realistic and theoretical corresponding point to achieve multi-source Point cloud data registration. Compared with the ICP algorithm for finding corresponding points in existing points, this method is more reasonable and more accurate, and can accurately correct low-precision point cloud in detail. The experimental results show that the accuracy of our method and the best algorithm is equivalent under the clean point cloud and point cloud of different resolutions. In the case of noise and distortion in the point cloud, our method is better than other algorithms. For low-precision point cloud, it can better match the target point cloud in detail, with better stability and robustness.

Research on Oil Painting Image Extraction and Identification Method based on Intelligent Vision

A high-precision and high-efficiency oil painting identification method is the auxiliary basis for authenticating works, because it can improve the efficiency and credibility of oil painting identification. Therefore, an oil painting image extraction method based on intelligent vision was proposed.An intelligent visual detection model was constructed to obtain the characteristics of oil painting images.The oil painting feature fusion method based on intelligent vision was adopted to integrate the color and shape features of oil painting features, calculate oil painting feature difference coefficient and difference feature threshold, and realize oil painting image extraction by oil painting image extraction rules.The research results verified that the proposed method could effectively identify the authenticity of oil paintings. Compared with the expert identification method and the identification method based on deep learning, it can be seen that the method had the highest identification accuracy, the shortest identification time, the best anti-interference, and the remarkable identification performance, so it had a high application value.

Multispectral Image Change Detection Based on Single-Band Slow Feature Analysis

Due to differences in external imaging conditions, multispectral images taken at different periods are subject to radiation differences, which severely affect the detection accuracy. To solve this problem, a modified algorithm based on slow feature analysis is proposed for multispectral image change detection. First, single-band slow feature analysis is performed to process bitemporal multispectral images band by band. In this way, the differences between unchanged pixels in each pair of single-band images can be sufficiently suppressed to obtain multiple feature-difference images containing real change information. Then, the feature-difference images of each band are fused into a grayscale distance image using the Euclidean distance. After Gaussian filtering of the grayscale distance image, false detection points can be further reduced. Finally, the k-means clustering method is performed on the filtered grayscale distance image to obtain the binary change map. Experiments reveal that our proposed algorithm is less affected by radiation differences and has obvious advantages in time complexity and detection accuracy.

Binocular fusion enhances the efficiency of spot-the-difference gameplay

Spot-the-difference, the popular childhood game and a prototypical change blindness task, involves identification of differences in local features of two otherwise identical scenes using an eye scanning and matching strategy. Through binocular fusion of the companion scenes, the game becomes a visual search task, wherein players can simply scan the cyclopean percept for local features that may distinctly stand-out due to binocular rivalry/lustre. Here, we had a total of 100 visually normal adult (18–28 years of age) volunteers play this game in the traditional non-fusion mode and after cross-fusion of the companion images using a hand-held mirror stereoscope. The results demonstrate that the fusion mode significantly speeds up gameplay and reduces errors, relative to the non-fusion mode, for a range of target sizes, contrasts, and chromaticity tested (all, p<0.001). Amongst the three types of local feature differences available in these images (polarity difference, presence/absence of a local feature difference and shape difference in a local feature difference), features containing polarity difference was identified as first in ~60–70% of instances in both modes of gameplay (p<0.01), with this proportion being larger in the fusion than in the non-fusion mode. The binocular fusion advantage is lost when the lustre cue is purposefully weakened through alterations in target luminance polarity. The spot-the-difference game may thus be cheated using binocular fusion and the differences readily identified through a vivid experience of binocular rivalry/lustre.

Composite Binary Pattern Assisted Micro-Expressions Spotting Through Feature Difference Analysis

Micro-Expressions (MEs) are one kind of facial movement which is very spontaneous and involuntary in nature. MEs are observed when a person attempts to hide or conceal the experiencing emotion in a high-stakes environment. The duration of ME is very short and approximately less than 500 milliseconds. Recognition of such kinds of expressions from lengthy video consequences to a limited Micro Expression Recognition Performance and also creates the computational burden. Hence, in this paper, we propose a new ME spotting (detection of ME frames) method based on a new texture descriptor called Composite Binary Pattern (CBP). As a pre-processing, we employ the viola jones algorithm for landmark regions detection followed by landmark points detection for facial alignment. Next, every aligned face is described through CBP and subjected to feature difference analysis followed by the threshold for ME spotting. For simulation, the REVIEW dataset is used and the performance is measured through Recall, Precision, and F-Score.

Expression of Story: Ethical considerations for participatory, community- and arts-based research relationships

INTRODUCTION: This meta-research article considers the ethics and efficacy of a nonviolent, “braided” methodology used by a research study called “The Recognition Project.” The methodology of The Recognition Project interweaved participatory, community-, and arts- based approaches in an effort to create a cooperative, relationally oriented environment where three distinct communities of interest could contribute respectively—and collaboratively—to the sharing, creation, and public dance performance of stories about self-harm. The three communities of interest were university-based researchers, community-based researchers who had engaged in self-harm, and an artist team of choreographers, a musician, and professional youth dancers. Our article explores some of the experiences, as shared by dancers of the artist team, from narrative interviews following the final dance performance.METHOD: Data were collected through qualitative interviews conducted with six artist team members. A qualitative thematic analysis approach was used to identify the main themes.FINDINGS: What emerged was an overriding theme about Story and the power issues that came forward due to the personal and the collective aspects of Story. The power issues were related to individual and collective exercise of power, the use of dialogue to build a positive community, and the transformative potential for the artist collaborators to participate in such a study.CONCLUSION: While participatory, community- and arts-based projects are often taken up with the intention of facilitating research that will not harm, there are important and additional ethical considerations to be made in community-based collaborations that feature difference across perspective, experience, skill, and knowledge.