8,829 research outputs found
Enhancement of Image Resolution by Binarization
Image segmentation is one of the principal approaches of image processing.
The choice of the most appropriate Binarization algorithm for each case proved
to be a very interesting procedure itself. In this paper, we have done the
comparison study between the various algorithms based on Binarization
algorithms and propose a methodologies for the validation of Binarization
algorithms. In this work we have developed two novel algorithms to determine
threshold values for the pixels value of the gray scale image. The performance
estimation of the algorithm utilizes test images with, the evaluation metrics
for Binarization of textual and synthetic images. We have achieved better
resolution of the image by using the Binarization method of optimum
thresholding techniques.Comment: 5 pages, 8 figure
Automatic Document Image Binarization using Bayesian Optimization
Document image binarization is often a challenging task due to various forms
of degradation. Although there exist several binarization techniques in
literature, the binarized image is typically sensitive to control parameter
settings of the employed technique. This paper presents an automatic document
image binarization algorithm to segment the text from heavily degraded document
images. The proposed technique uses a two band-pass filtering approach for
background noise removal, and Bayesian optimization for automatic
hyperparameter selection for optimal results. The effectiveness of the proposed
binarization technique is empirically demonstrated on the Document Image
Binarization Competition (DIBCO) and the Handwritten Document Image
Binarization Competition (H-DIBCO) datasets
Automatic Crack Detection in Built Infrastructure Using Unmanned Aerial Vehicles
This paper addresses the problem of crack detection which is essential for
health monitoring of built infrastructure. Our approach includes two stages,
data collection using unmanned aerial vehicles (UAVs) and crack detection using
histogram analysis. For the data collection, a 3D model of the structure is
first created by using laser scanners. Based on the model, geometric properties
are extracted to generate way points necessary for navigating the UAV to take
images of the structure. Then, our next step is to stick together those
obtained images from the overlapped field of view. The resulting image is then
clustered by histogram analysis and peak detection. Potential cracks are
finally identified by using locally adaptive thresholds. The whole process is
automatically carried out so that the inspection time is significantly improved
while safety hazards can be minimised. A prototypical system has been developed
for evaluation and experimental results are included.Comment: In proceeding of The 34th International Symposium on Automation and
Robotics in Construction (ISARC), pp. 823-829, Taipei, Taiwan, 201
Investigation of image enhancement techniques for the development of a self-contained airborne radar navigation system
This study was devoted to an investigation of the feasibility of applying advanced image processing techniques to enhance radar image characteristics that are pertinent to the pilot's navigation and guidance task. Millimeter (95 GHz) wave radar images for the overwater (i.e., offshore oil rigs) and overland (Heliport) scenario were used as a data base. The purpose of the study was to determine the applicability of image enhancement and scene analysis algorithms to detect and improve target characteristics (i.e., manmade objects such as buildings, parking lots, cars, roads, helicopters, towers, landing pads, etc.) that would be helpful to the pilot in determining his own position/orientation with respect to the outside world and assist him in the navigation task. Results of this study show that significant improvements in the raw radar image may be obtained using two dimensional image processing algorithms. In the overwater case, it is possible to remove the ocean clutter by thresholding the image data, and furthermore to extract the target boundary as well as the tower and catwalk locations using noise cleaning (e.g., median filter) and edge detection (e.g., Sobel operator) algorithms
Performance assessment of time–frequency RFI mitigation techniques in microwave radiometry
©2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Radio–frequency interference (RFI) signals are a well-known threat for microwave radiometry (MWR) applications. In order to alleviate this problem, different approaches for RFI detection and mitigation are currently under development. Since RFI signals are man made, they tend to have their power more concentrated in the time–frequency (TF) space as compared to naturally emitted noise. The aim of this paper is to perform an assessment of different TF RFI mitigation techniques in terms of probability of detection, resolution loss (RL), and mitigation performance. In this assessment, six different kinds of RFI signals have been considered: a glitch, a burst of pulses, a wide-band chirp, a narrow-band chirp, a continuous wave, and a wide-band modulation. The results show that the best performance occurs when the transform basis has a similar shape as compared to the RFI signal. For the best case performance, the maximum residual RFI temperature is 14.8 K, and the worst RL is 8.4%. Moreover, the multiresolution Fourier transform technique appears as a good tradeoff solution among all other techniques since it can mitigate all RFI signals under evaluation with a maximum residual RFI temperature of 21 K, and a worst RL of 26.3%. Although the obtained results are still far from an acceptable bias Misplaced < 1 K for MWR applications, there is still work to do in a combined test using the information gathered simultaneously by all mitigation techniques, which could improve the overall performance of RFI mitigation.Peer ReviewedPostprint (author's final draft
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