scholarly journals Center Symmetric Local Multilevel Pattern Based Descriptor and Its Application in Image Matching

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Hui Zeng ◽  
Xiuqing Wang ◽  
Yu Gu
Keyword(s):  
Computational Efficiency ◽  
Image Matching ◽  
State Of The Art ◽  
Experimental Results ◽  
Image Region ◽  
Local Intensity ◽  
Region Description ◽  
Local Image

This paper presents an effective local image region description method, called CS-LMP (Center Symmetric Local Multilevel Pattern) descriptor, and its application in image matching. The CS-LMP operator has no exponential computations, so the CS-LMP descriptor can encode the differences of the local intensity values using multiply quantization levels without increasing the dimension of the descriptor. Compared with the binary/ternary pattern based descriptors, the CS-LMP descriptor has better descriptive ability and computational efficiency. Extensive image matching experimental results testified the effectiveness of the proposed CS-LMP descriptor compared with other existing state-of-the-art descriptors.

An Image Region Description Method Based on Step Sector Statistics and its Application in Image Copy-Rotate/Flip-Move Forgery Detection

2012 ◽  
Vol 4 (1) ◽  
pp. 49-62 ◽  
Author(s):  
Likai Chen ◽  
Wei Lu ◽  
Jiangqun Ni
Keyword(s):  
Radial Direction ◽  
Rotation Angle ◽  
Experimental Results ◽  
Robust Method ◽  
Forgery Detection ◽  
Image Region ◽  
Feature Description ◽  
Region Description ◽  
Region Feature ◽  
Local Image

A robust method for local image region feature description based on step sector statistics is proposed in this paper. The means and the standard deviations along the radial direction of the circle image region are extracted through the sector masks, and the rearrangement of these statistics makes this image region description method rotation-robust. The proposed description method is applied in the detection of copy-rotate-move forgery, and it can detect the exact rotation angle between the duplicate regions. With minor extension, the proposed description method can also be applied in the detection of copy-flip-move forgery. The experimental results show that the proposed description method can work well for the detection of copy-rotate/flip-move forgery.

An Image Region Description Method Based on Step Sector Statistics and its Application in Image Copy-Rotate/Flip-Move Forgery Detection

2013 ◽  
pp. 35-49
Author(s):  
Likai Chen ◽  
Wei Lu ◽  
Jiangqun Ni
Keyword(s):  
Radial Direction ◽  
Rotation Angle ◽  
Experimental Results ◽  
Robust Method ◽  
Forgery Detection ◽  
Image Region ◽  
Feature Description ◽  
Region Description ◽  
Region Feature ◽  
Local Image

A robust method for local image region feature description based on step sector statistics is proposed in this paper. The means and the standard deviations along the radial direction of the circle image region are extracted through the sector masks, and the rearrangement of these statistics makes this image region description method rotation-robust. The proposed description method is applied in the detection of copy-rotate-move forgery, and it can detect the exact rotation angle between the duplicate regions. With minor extension, the proposed description method can also be applied in the detection of copy-flip-move forgery. The experimental results show that the proposed description method can work well for the detection of copy-rotate/flip-move forgery.

scholarly journals NICE: Superpixel Segmentation Using Non-Iterative Clustering with Efficiency

2020 ◽  
Vol 10 (12) ◽  
pp. 4415 ◽  
Author(s):  
Cheng Li ◽  
Baolong Guo ◽  
Geng Wang ◽  
Yan Zheng ◽  
Yang Liu ◽  
...  
Keyword(s):  
Computer Vision ◽  
Computational Efficiency ◽  
Batch Processing ◽  
Experimental Results ◽  
Processing Strategy ◽  
Trade Off ◽  
Quantitative Metrics ◽  
Visual Tasks ◽  
Pixel Correlation ◽  
Region Description

Superpixels intuitively over-segment an image into small compact regions with homogeneity. Owing to its outstanding performance on region description, superpixels have been widely used in various computer vision tasks as the substitution for pixels. Therefore, efficient algorithms for generating superpixels are still important for advanced visual tasks. In this work, two strategies are presented on conventional simple non-iterative clustering (SNIC) framework, aiming to improve the computational efficiency as well as segmentation performance. Firstly, inter-pixel correlation is introduced to eliminate the redundant inspection of neighboring elements. In addition, it strengthens the color identity in complicated texture regions, thus providing a desirable trade-off between runtime and accuracy. As a result, superpixel centroids are evolved more efficiently and accurately. For further accelerating the framework, a recursive batch processing strategy is proposed to eliminate unnecessary sorting operations. Therefore, a large number of neighboring elements can be assigned directly. Finally, the two strategies result in a novel synergetic non-iterative clustering with efficiency (NICE) method based on SNIC. Experimental results verify that it works 40% faster than conventional framework, while generating comparable superpixels for several quantitative metrics—sometimes even better.

scholarly journals An Improved Fingerprinting Algorithm for Detection of Video Frame Duplication Forgery

2012 ◽  
Vol 4 (3) ◽  
pp. 20-32 ◽  
Author(s):  
Yongjian Hu ◽  
Chang-Tsun Li ◽  
Yufei Wang ◽  
Bei-bei Liu
Keyword(s):  
Computational Efficiency ◽  
State Of The Art ◽  
Experimental Results ◽  
Video Frame ◽  
Detection Accuracy ◽  
Forgery Detection ◽  
Detection Algorithms ◽  
Dct Coefficients ◽  
Duplication Detection ◽  
Frame Duplication

Frame duplication is a common way of digital video forgeries. State-of-the-art approaches of duplication detection usually suffer from heavy computational load. In this paper, the authors propose a new algorithm to detect duplicated frames based on video sub-sequence fingerprints. The fingerprints employed are extracted from the DCT coefficients of the temporally informative representative images (TIRIs) of the sub-sequences. Compared with other similar algorithms, this study focuses on improving fingerprints representing video sub-sequences and introducing a simple metric for the matching of video sub-sequences. Experimental results show that the proposed algorithm overall outperforms three related duplication forgery detection algorithms in terms of computational efficiency, detection accuracy and robustness against common video operations like compression and brightness change.

Local image region description using orthogonal symmetric local ternary pattern

2015 ◽  
Vol 54 ◽  
pp. 56-62 ◽  
Author(s):  
Mingming Huang ◽  
Zhichun Mu ◽  
Hui Zeng ◽  
Shuai Huang
Keyword(s):  
Image Region ◽  
Local Ternary Pattern ◽  
Region Description ◽  
Local Image

Browser Security Attacks and Detection Techniques: A Case of Tabnabbing

2020 ◽  
Vol 8 (1) ◽  
pp. 33-41
Author(s):  
Dr. S. Sarika ◽  
Keyword(s):  
Credit Card ◽  
State Of The Art ◽  
Experimental Results ◽  
Detection Technique ◽  
Security Attacks ◽  
Agent Based ◽  
Detection Techniques ◽  
Browser Security ◽  
Cyber Threats ◽  
Multi Agent

Phishing is a malicious and deliberate act of sending counterfeit messages or mimicking a webpage. The goal is either to steal sensitive credentials like login information and credit card details or to install malware on a victim’s machine. Browser-based cyber threats have become one of the biggest concerns in networked architectures. The most prolific form of browser attack is tabnabbing which happens in inactive browser tabs. In a tabnabbing attack, a fake page disguises itself as a genuine page to steal data. This paper presents a multi agent based tabnabbing detection technique. The method detects heuristic changes in a webpage when a tabnabbing attack happens and give a warning to the user. Experimental results show that the method performs better when compared with state of the art tabnabbing detection techniques.

scholarly journals Automatic Detection of Discrimination Actions from Social Images

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 325
Author(s):  
Zhihao Wu ◽  
Baopeng Zhang ◽  
Tianchen Zhou ◽  
Yan Li ◽  
Jianping Fan
Keyword(s):  
Action Recognition ◽  
State Of The Art ◽  
Automatic Detection ◽  
Experimental Results ◽  
Practical Approach ◽  
Detection And Identification ◽  
Art Methods ◽  
Image Set ◽  
Social Images ◽  
Relationship Identification

In this paper, we developed a practical approach for automatic detection of discrimination actions from social images. Firstly, an image set is established, in which various discrimination actions and relations are manually labeled. To the best of our knowledge, this is the first work to create a dataset for discrimination action recognition and relationship identification. Secondly, a practical approach is developed to achieve automatic detection and identification of discrimination actions and relationships from social images. Thirdly, the task of relationship identification is seamlessly integrated with the task of discrimination action recognition into one single network called the Co-operative Visual Translation Embedding++ network (CVTransE++). We also compared our proposed method with numerous state-of-the-art methods, and our experimental results demonstrated that our proposed methods can significantly outperform state-of-the-art approaches.

scholarly journals Multi-Sensor Fusion for Aerial Robots in Industrial GNSS-Denied Environments

2021 ◽  
Vol 11 (9) ◽  
pp. 3921
Author(s):  
Paloma Carrasco ◽  
Francisco Cuesta ◽  
Rafael Caballero ◽  
Francisco J. Perez-Grau ◽  
Antidio Viguria
Keyword(s):  
Sensor Fusion ◽  
Computational Efficiency ◽  
Probabilistic Approach ◽  
Laser Scanner ◽  
Industrial Applications ◽  
Experimental Results ◽  
Added Value ◽  
Aerial Robots ◽  
3D Localization ◽  
High Level

The use of unmanned aerial robots has increased exponentially in recent years, and the relevance of industrial applications in environments with degraded satellite signals is rising. This article presents a solution for the 3D localization of aerial robots in such environments. In order to truly use these versatile platforms for added-value cases in these scenarios, a high level of reliability is required. Hence, the proposed solution is based on a probabilistic approach that makes use of a 3D laser scanner, radio sensors, a previously built map of the environment and input odometry, to obtain pose estimations that are computed onboard the aerial platform. Experimental results show the feasibility of the approach in terms of accuracy, robustness and computational efficiency.

scholarly journals PyConvU-Net: a lightweight and multiscale network for biomedical image segmentation

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Changyong Li ◽  
Yongxian Fan ◽  
Xiaodong Cai
Keyword(s):  
Image Segmentation ◽  
Deep Learning ◽  
State Of The Art ◽  
Experimental Results ◽  
Actual Situation ◽  
Controlled Experiments ◽  
Biomedical Image ◽  
Segmentation Methods ◽  
Art Performance

Abstract Background With the development of deep learning (DL), more and more methods based on deep learning are proposed and achieve state-of-the-art performance in biomedical image segmentation. However, these methods are usually complex and require the support of powerful computing resources. According to the actual situation, it is impractical that we use huge computing resources in clinical situations. Thus, it is significant to develop accurate DL based biomedical image segmentation methods which depend on resources-constraint computing. Results A lightweight and multiscale network called PyConvU-Net is proposed to potentially work with low-resources computing. Through strictly controlled experiments, PyConvU-Net predictions have a good performance on three biomedical image segmentation tasks with the fewest parameters. Conclusions Our experimental results preliminarily demonstrate the potential of proposed PyConvU-Net in biomedical image segmentation with resources-constraint computing.

Sign in / Sign up

Export Citation Format

Share Document