scholarly journals Entropy-Based Maximally Stable Extremal Regions for Robust Feature Detection

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Huiwen Cai ◽  
Xiaoyan Wang ◽  
Ming Xia ◽  
Yangsheng Wang
Keyword(s):  
Probability Distribution Function ◽  
Feature Detection ◽  
State Of The Art ◽  
Computational Effort ◽  
Local Region ◽  
Regional Area ◽  
Image Blurring ◽  
Blurred Image ◽  
The Stability ◽  
Blurred Images

Maximally stable extremal regions (MSER) is a state-of-the-art method in local feature detection. However, this method is sensitive to blurring because, in blurred images, the intensity values in region boundary will vary more slowly, and this will undermine the stability criterion that the MSER relies on. In this paper, we propose a method to improve MSER, making it more robust to image blurring. To find back the regions missed by MSER in the blurred image, we utilize the fact that the entropy of probability distribution function of intensity values increases rapidly when the local region expands across the boundary, while the entropy in the central part remains small. We use the entropy averaged by the regional area as a measure to reestimate regions missed by MSER. Experiments show that, when dealing with blurred images, the proposed method has better performance than the original MSER, with little extra computational effort.

Recognition of Birds in Blurred and Illumination Images by Local Features

2017 ◽  
Vol 7 (7) ◽  
pp. 243
Author(s):  
Suresha .M ◽  
. Sandeep
Keyword(s):  
Computer Vision ◽  
Time Complexity ◽  
Feature Detection ◽  
Feature Matching ◽  
Fast Algorithms ◽  
Local Features ◽  
Experimental Demonstration ◽  
Harris Corner ◽  
Blurred Image ◽  
Blurred Images

Local features are of great importance in computer vision. It performs feature detection and feature matching are two important tasks. In this paper concentrates on the problem of recognition of birds using local features. Investigation summarizes the local features SURF, FAST and HARRIS against blurred and illumination images. FAST and Harris corner algorithm have given less accuracy for blurred images. The SURF algorithm gives best result for blurred image because its identify strongest local features and time complexity is less and experimental demonstration shows that SURF algorithm is robust for blurred images and the FAST algorithms is suitable for images with illumination.

A Motion Blurred Image Restoration Method Based on Wiener Filtering

2011 ◽  
Vol 403-408 ◽  
pp. 1664-1667 ◽  
Author(s):  
Qian Qian Quan
Keyword(s):  
Image Restoration ◽  
Motion Blur ◽  
Experimental Results ◽  
Wiener Filtering ◽  
Degradation Model ◽  
Image Blurring ◽  
Blurred Image ◽  
Working Principle ◽  
Restoration Method ◽  
Blurred Images

To the deficiencies of traditional methods for avoiding motion image blurring, a motion blur image restoration method is studied based on Wiener filtering in this paper. The formation factors of motion-blurred images and the imaging process are analyzed, and the motion blur degradation model is established. It introduced the working principle of Wiener filtering, described the steps of blurred image restoration in details. The experiment testing and data analyzing are also conducted. Experimental results showed that the method can has good performance.

scholarly journals Quantum-mechanical hydration plays critical role in the stability of firefly oxyluciferin isomers: State-of-the-art calculations of the excited states

2020 ◽  
Vol 153 (20) ◽  
pp. 201103
Author(s):  
Yoshifumi Noguchi ◽  
Miyabi Hiyama ◽  
Motoyuki Shiga ◽  
Hidefumi Akiyama ◽  
Osamu Sugino
Keyword(s):  
Excited States ◽  
State Of The Art ◽  
Critical Role ◽  
Quantum Mechanical ◽  
The Stability

Numerical Investigation of the Solidity Effect on Linear Compressor Cascades

2014 ◽  
Author(s):  
J. Sans ◽  
M. Resmini ◽  
J.-F. Brouckaert ◽  
S. Hiernaux
Keyword(s):  
Numerical Investigation ◽  
State Of The Art ◽  
Leading Edge ◽  
Operating Conditions ◽  
Compressor Cascade ◽  
Minimum Loss ◽  
Low Speed ◽  
High Mach ◽  
The Stability ◽  
The Impact

Solidity in compressors is defined as the ratio of the aerodynamic chord over the peripheral distance between two adjacent blades, the pitch. This parameter is simply the inverse of the pitch-to-chord ratio generally used in turbines. Solidity must be selected at the earliest design phase, i.e. at the level of the meridional design and represents a crucial step in the whole design process. Most of the existing studies on this topic rely on low-speed compressor cascade correlations from Carter or Lieblein. The aim of this work is to update those correlations for state-of-the-art controlled diffusion blades, and extend their application to high Mach number flow regimes more typical of modern compressors. Another objective is also to improve the physical understanding of the solidity effect on compressor performance and stability. A numerical investigation has been performed using the commercial software FINE/Turbo. Two different blade profiles were selected and investigated in the compressible flow regime as an extension to the low-speed data on which the correlations are based. The first cascade uses a standard double circular arc profile, extensively referenced in the literature, while the second configuration uses a state-of-the-art CDB, representative of low pressure compressor stator mid-span profile. Both profiles have been designed with the same inlet and outlet metal angles and the same maximum thickness but the camber and thickness distributions, the stagger angle and the leading edge geometry of the CDB have been optimized. The determination of minimum loss, optimum incidence and deviation is addressed and compared with existing correlations for both configurations and various Mach numbers that have been selected in order to match typical booster stall and choke operating conditions. The emphasis is set on the minimum loss performance at mid-span. The impact of the solidity on the operating range and the stability of the cascade are also studied.

scholarly journals An Image Copy-Move Forgery Detection Scheme Based on A-KAZE and SURF Features

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 706 ◽  
Author(s):  
Chengyou Wang ◽  
Zhi Zhang ◽  
Xiao Zhou
Keyword(s):  
Feature Detection ◽  
Joint Photographic Expert Group ◽  
Social Stability ◽  
Forgery Detection ◽  
Detection Scheme ◽  
Speeded Up Robust Features ◽  
Image Blurring ◽  
Surf Features ◽  
Copy Move Forgery Detection ◽  
Processing Techniques

The popularity of image editing software has made it increasingly easy to alter the content of images. These alterations threaten the authenticity and integrity of images, causing misjudgments and possibly even affecting social stability. The copy-move technique is one of the most commonly used approaches for manipulating images. As a defense, the image forensics technique has become popular for judging whether a picture has been tampered with via copy-move, splicing, or other forgery techniques. In this paper, a scheme based on accelerated-KAZE (A-KAZE) and speeded-up robust features (SURF) is proposed for image copy-move forgery detection (CMFD). It is difficult for most keypoint-based CMFD methods to obtain sufficient points in smooth regions. To remedy this defect, the response thresholds for the A-KAZE and SURF feature detection stages are set to small values in the proposed method. In addition, a new correlation coefficient map is presented, in which the duplicated regions are demarcated, combining filtering and mathematical morphology operations. Numerous experiments are conducted to demonstrate the effectiveness of the proposed method in searching for duplicated regions and its robustness against distortions and post-processing techniques, such as noise addition, rotation, scaling, image blurring, joint photographic expert group (JPEG) compression, and hybrid image manipulation. The experimental results demonstrate that the performance of the proposed scheme is superior to that of other tested CMFD methods.

scholarly journals Obscure Image Classification and Restoration using Support Vector Machines

2019 ◽  
Vol 8 (4) ◽  
pp. 8231-8236
Keyword(s):  
Kernel Estimation ◽  
Classification Algorithm ◽  
Support Vector ◽  
Svm Classification ◽  
Vector Machines ◽  
Blurred Image ◽  
Simulation Results ◽  
Blurred Images ◽  
Identification And Characterization ◽  
Restoration Model

A restoration and classification computation for blurred image which depends on obscure identification and characterization is proposed in this paper. Initially, new obscure location calculation is proposed to recognize the Gaussian, Motion and Defocus based blurred locales in the image. The degradation-restoration model referred with pre-processing followed by binarization and features extraction/classification algorithm applied on obscure images. At this point, support vector machine (SVM) classification algorithm is proposed to cluster the blurred images. Once the obscure class of the locales is affirmed, the structure of the obscure kernels of the blurred images are affirmed. At that point, the obscure kernel estimation techniques are embraced to appraise the obscure kernels. At last, the blurred locales are re-established utilizing nonblind image deblurring calculation and supplant the blurred images with the restored images. The simulation results demonstrate that the proposed calculation performs well

scholarly journals Temperature Effects on Optical Trapping Stability

Micromachines ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 954
Author(s):  
Dasheng Lu ◽  
Francisco Gámez ◽  
Patricia Haro-González
Keyword(s):  
Brownian Motion ◽  
Environmental Conditions ◽  
Temperature Effects ◽  
Room Temperature ◽  
Optical Trapping ◽  
State Of The Art ◽  
Thermal Sensing ◽  
The Stability ◽  
Object Of Study ◽  
Optically Trapped

In recent years, optically trapped luminescent particles have emerged as a reliable probe for contactless thermal sensing because of the dependence of their luminescence on environmental conditions. Although the temperature effect in the optical trapping stability has not always been the object of study, the optical trapping of micro/nanoparticles above room temperature is hindered by disturbances caused by temperature increments of even a few degrees in the Brownian motion that may lead to the release of the particle from the trap. In this report, we summarize recent experimental results on thermal sensing experiments in which micro/nanoparticles are used as probes with the aim of providing the contemporary state of the art about temperature effects in the stability of potential trapping processes.

scholarly journals Commonsense Reasoning to Guide Deep Learning for Scene Understanding (Extended Abstract)

2020 ◽  
Author(s):  
Mohan Sridharan ◽  
Tiago Mota
Keyword(s):  
Domain Knowledge ◽  
Inductive Learning ◽  
Network Models ◽  
Computational Effort ◽  
Partial Occlusion ◽  
Commonsense Reasoning ◽  
Deep Networks ◽  
Training Examples ◽  
The Stability ◽  
Simulated Images

Our architecture uses non-monotonic logical reasoning with incomplete commonsense domain knowledge, and incremental inductive learning, to guide the construction of deep network models from a small number of training examples. Experimental results in the context of a robot reasoning about the partial occlusion of objects and the stability of object configurations in simulated images indicate an improvement in reliability and a reduction in computational effort in comparison with an architecture based just on deep networks.

The Stability-Limiting Flow Mechanisms in a Subsonic Axial-Flow Compressor and Its Passive Control With Casing Treatment

2008 ◽  
Author(s):  
Xingen Lu ◽  
Junqiang Zhu ◽  
Chaoqun Nie ◽  
Weiguang Huang
Keyword(s):  
Flow Instability ◽  
State Of The Art ◽  
Axial Flow ◽  
Flow Mechanism ◽  
Blade Passage ◽  
Casing Treatment ◽  
Compressor Rotor ◽  
Flow Compressor ◽  
The Stability ◽  
End Wall

The phenomenon of flow instability in the compression system such as fan and compressor has been a long-standing “bottle-neck” problem for gas turbines/aircraft engines. With a vision of providing a state-of-the-art understanding of the flow field in axial-flow compressor in the perspective of enhancing their stability using passive means. Two topics are covered in this paper. The first topic is the stability-limiting flow mechanism close to stall, which is the basic knowledge needed to manipulate end-wall flow behavior for the stability improvement. The physical process occurring when approaching stall and the role of complex tip flow mechanism on flow instability in current high subsonic axial compressor rotor has been assessed using single blade passage computations. The second topic is flow instability manipulation with casing treatment. In order to advance the understanding of the fundamental mechanisms of casing treatment and determine the change in the flow field by which casing treatment improve compressor stability, systematic studies of the coupled flow through a subsonic compressor rotor and various end-wall treatments were carried out using a state-of-the-art multi-block flow solver. The numerically obtained flow fields were interrogated to identify complicated flow phenomenon around and within the end-wall treatments and describe the interaction between the rotor tip flow and end-wall treatments. Detailed analyses of the flow visualization at the rotor tip have exposed the different tip flow topologies between the cases with treatment casing and with untreated smooth wall. It was found that the primary stall margin enhancement afforded by end-wall treatments is a result of the tip flow manipulation. Compared to the smooth wall case, the treated casing significantly dampen or absorb the blockage near the upstream part of the blade passage caused by the upstream movement of tip clearance flow and weakens the roll-up of the core vortex. These mechanisms prevent an early spillage of low momentum fluid into the adjacent blade passage and delay the onset of flow instability.

Restoration of Motion Blurred Image Based on PSO Combine Wiener Filter in Ship Imaging System

2014 ◽  
Vol 1006-1007 ◽  
pp. 739-742
Author(s):  
Hui Xuan Fu ◽  
Yu Chao Wang ◽  
Xun Su
Keyword(s):  
Imaging System ◽  
Search Algorithm ◽  
Wiener Filter ◽  
Optimal Solution ◽  
Parameter Selection ◽  
Improve Image Quality ◽  
Blurred Image ◽  
Blurred Images ◽  
Ringing Effect

Ship internal equipment vibration will cause the imaging system platform vibration, resulting in blurred images. Wiener Filter is often used to restore the motion blurred image. The principle of the method expects to minimize the mean square error between the restore image and original image. However, this method has some constrains, if parameter selection improper, it generates ringing effect easily. Usually, most users select parameter by rule of thumb, so they frequently fail to generate the optimal solution. In order to get high quality restore image, eliminate the ringing effect, a new approach based on particle swarm optimization (PSO) Wiener Filter was proposed, which automatically adjusts the parameter for Wiener Filter, this method seek the optimal solution by transferring information between individuals and information sharing, which is a highly efficient parallel search algorithm, insuring the accuracy of parameter selection, effectively reducing the ringing effect after image restoration, improve image quality of restoration.

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