scholarly journals Design and Comparison of Image Hashing Methods: A Case Study on Cork Stopper Unique Identification

2021 ◽  
Vol 7 (3) ◽  
pp. 48
Author(s):  
Ricardo Fitas ◽  
Bernardo Rocha ◽  
Valter Costa ◽  
Armando Sousa
Keyword(s):  
Wavelet Transform ◽  
Image Matching ◽  
Comparison Method ◽  
Cork Stopper ◽  
Image Hashing ◽  
Accuracy Rate ◽  
Matching Problem ◽  
Successful Approach ◽  
Cork Stoppers

Cork stoppers were shown to have unique characteristics that allow their use for authentication purposes in an anti-counterfeiting effort. This authentication process relies on the comparison between a user’s cork image and all registered cork images in the database of genuine items. With the growth of the database, this one-to-many comparison method becomes lengthier and therefore usefulness decreases. To tackle this problem, the present work designs and compares hashing-assisted image matching methods that can be used in cork stopper authentication. The analyzed approaches are the discrete cosine transform, wavelet transform, Radon transform, and other methods such as difference hash and average hash. The most successful approach uses a 1024-bit hash length and difference hash method providing a 98% accuracy rate. By transforming the image matching into a hash matching problem, the approach presented becomes almost 40 times faster when compared to the literature.

Catching an Atom Spy: MI5 and the Investigation of Klaus Fuchs

2010 ◽  
pp. 554-567
Author(s):  
Timothy Gibbs
Keyword(s):  
Cold War ◽  
High Risk ◽  
Klaus Fuchs ◽  
Key Issues ◽  
Successful Approach ◽  
Anglo American ◽  
Atomic Espionage ◽  
Signals Intelligence

This article focuses on M15 organization and Klaus Fuchs, a German-born physicist and Soviet “Atom Spy” who was arrested in 1950 and served fourteen years for offences related to atomic espionage. It examines how Fuchs was identified as an “Atom Spy” in 1949 and describes the MI5's investigation, which ended in the early 1950 with the successful arrest, prosecution, and imprisonment of this highly significant Cold War figure. Key issues discussed in this article include the difficulties encountered by MI5 and the budding British atomic program in the sphere of security. It also discusses the role of Signals intelligence (SIGINT) in the investigation of Fuchs, and the high-risk but ultimately successful approach taken by MI5's key interrogator, William Skardon. This case study highlights both the unparalleled level of international intelligence cooperation between the British agencies and their American counterparts, which made the resolution of this case possible, and some of the frailties in the Anglo-American alliance that were brought to the fore by the exposure of Fuchs as an Atom Spy.

Pigeon-inspired optimization and lateral inhibition for image matching of autonomous aerial refueling

2017 ◽  
Vol 232 (8) ◽  
pp. 1571-1583 ◽  
Author(s):  
Yongbin Sun ◽  
Haibin Duan
Keyword(s):  
Particle Swarm Optimization ◽  
Lateral Inhibition ◽  
Image Matching ◽  
Hybrid Algorithm ◽  
Particle Swarm ◽  
Matching Problem ◽  
Aerial Refueling ◽  
Swarm Optimization ◽  
Swarm Intelligence Algorithm ◽  
Computation Speed

Autonomous aerial refueling (AAR) is an essential application of unmanned aerial vehicles for both military and civilian domains. In this paper, a hybrid algorithm of the pigeon-inspired optimization (PIO) and lateral inhibition (LI), called LI-PIO, is proposed for image matching problem of AAR. LI is adopted for image pre-processing to enhance the edges and contrast of images. PIO, inspired from the homing characteristics of pigeons, is a novel bio-inspired swarm intelligence algorithm. To demonstrate the effectiveness and feasibility of our proposed algorithm, we make extensive comparative experiments with particle swarm optimization (PSO), particle swarm optimization based on lateral inhibition (LI-PSO), and PIO. It can be concluded from the experimental results that our proposed LI-PIO has excellent performances for image matching problem of AAR, especially in convergent rate and computation speed.

scholarly journals A CASE STUDY ON THROUGH-WATER DENSE IMAGE MATCHING

2018 ◽  
Vol XLII-2 ◽  
pp. 659-666 ◽  
Author(s):  
G. Mandlburger
Keyword(s):  
Image Matching ◽  
Water Surface ◽  
Point Clouds ◽  
Water Clarity ◽  
Aerial Images ◽  
Mean Deviation ◽  
Range Image ◽  
Surface Mapping ◽  
Dense Image

In the last years, the tremendous progress in image processing and camera technology has reactivated the interest in photogrammetrybased surface mapping. With the advent of Dense Image Matching (DIM), the derivation of height values on a per-pixel basis became feasible, allowing the derivation of Digital Elevation Models (DEM) with a spatial resolution in the range of the ground sampling distance of the aerial images, which is often below 10 cm today. While mapping topography and vegetation constitutes the primary field of application for image based surface reconstruction, multi-spectral images also allow to see through the water surface to the bottom underneath provided sufficient water clarity. In this contribution, the feasibility of through-water dense image matching for mapping shallow water bathymetry using off-the-shelf software is evaluated. In a case study, the SURE software is applied to three different coastal and inland water bodies. After refraction correction, the DIM point clouds and the DEMs derived thereof are compared to concurrently acquired laser bathymetry data. The results confirm the general suitability of through-water dense image matching, but sufficient bottom texture and favorable environmental conditions (clear water, calm water surface) are a preconditions for achieving accurate results. Water depths of up to 5 m could be mapped with a mean deviation between laser and trough-water DIM in the dm-range. Image based water depth estimates, however, become unreliable in case of turbid or wavy water and poor bottom texture.

scholarly journals HOUGH TRANSFORM GENERATED STRONG IMAGE HASHING SCHEME FOR COPY DETECTION

2018 ◽  
Author(s):  
Mayank Srivastava ◽  
Jamshed M Siddiqui ◽  
Mohammad Athar Ali
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Hough Transform ◽  
Rapid Development ◽  
Discrimination Performance ◽  
Discrete Wavelet ◽  
Image Hashing ◽  
Copy Detection ◽  
Detection Scheme

The rapid development of image editing software has resulted in widespread unauthorized duplication of original images. This has given rise to the need to develop robust image hashing technique which can easily identify duplicate copies of the original images apart from differentiating it from different images. In this paper, we have proposed an image hashing technique based on discrete wavelet transform and Hough transform, which is robust to large number of image processing attacks including shifting and shearing. The input image is initially pre-processed to remove any kind of minor effects. Discrete wavelet transform is then applied to the pre-processed image to produce different wavelet coefficients from which different edges are detected by using a canny edge detector. Hough transform is finally applied to the edge-detected image to generate an image hash which is used for image identification. Different experiments were conducted to show that the proposed hashing technique has better robustness and discrimination performance as compared to the state-of-the-art techniques. Normalized average mean value difference is also calculated to show the performance of the proposed technique towards various image processing attacks. The proposed copy detection scheme can perform copy detection over large databases and can be considered to be a prototype for developing online real-time copy detection system.   

scholarly journals A Case Study of Assessing Button Bits Failure through Wavelet Transform Using Rock Drilling Induced Noise Signals

2017 ◽  
Vol 06 (01) ◽  
Author(s):  
Kawamura Y ◽  
Jang H ◽  
Hettiarachchi DS ◽  
Takarada Y ◽  
Okawa H ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Rock Drilling
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