scholarly journals Comprehensive Analysis of Edge Detection in Color Image Processing

2021 ◽  
Author(s):  
Konstantinos N Plataniotis ◽  
Zhu, Shu-Yu ◽  
Anastasios N. Venetsanopoulos
Keyword(s):  
Edge Detection ◽  
Order Statistic ◽  
Color Image ◽  
Detailed Comparison ◽  
Distance Measures ◽  
Difference Vector ◽  
Detection Techniques ◽  
Special Cases ◽  
Edge Detectors ◽  
The Difference

Various approaches to edge detection for color images, including techniques extended from monochrome edge detection as well as vector space approaches, are examined. In particular, edge detection techniques based on vector order statistic operators and difference vector operators are studied in detail. Numerous edge detectors are obtained as special cases of these two classes of operators. The effect of distance measures on the performance of different color edge detectors is studied by employing distance measures other than the Euclidean norm. Variations are introduced to both the vector order statistic opera-tors and the difference vector operators to improve noise performance. They both demonstrate the ability to attenuate noise with added algorithm complexity. Among them, the difference vector operator with adaptive filtering shows the most promising results. Other vector directional filtering techniques are also introduced and utilized for color edge detection. Both quantitative and subjective tests are performed in evaluating the performance of the edge detectors, and a detailed comparison is presented.<div>Copyright 1999 Society of Photo‑Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited.<br></div><div><br></div>

Early Fire Detection of Large Space Combining Thresholding with Edge Detection Techniques

2010 ◽  
Vol 44-47 ◽  
pp. 2060-2064
Author(s):  
Guo Liang Hu ◽  
Xi Jiang
Keyword(s):  
Image Segmentation ◽  
Edge Detection ◽  
Fire Detection ◽  
Image Features ◽  
Large Space ◽  
Detection Techniques ◽  
Edge Detectors ◽  
Otsu’S Method ◽  
Image Edges ◽  
Early Fire Detection

Image segmentation is a crucial step of the early fire detection in large space based on image processing technology. The image edges contain abundant feature information, and the edge detection has been a main topic of image segmentation algorithm. In this paper, several kinds of traditional edge detectors have been used to detect the edge of frame target in the fire video images, and the results have been contrasted and analyzed. Considering the influence of breaks in the edge caused by noise, nonuniform illumination and spurious intensity discontinuities, proposing the method of combining thresholding with edge detection, using Otsu’s method to compute a threshold for segmentation, extracting the flame area from the background, and then using the traditional edge detectors to detect the flame edge. At the same time, the simulation results based on the MATLAB kits indicate that this kind of method has good effectiveness and strong robustness, the detected flame edges have better effect in integrality and definition, and the relevant result can be the basis of the subsequent extraction and analysis of the fire image features as well as the space positioning of the fire.

scholarly journals Edge Detection Using Distinct Particle Swarm Optimization

2019 ◽  
Vol 8 (9) ◽  
pp. 1050-1057
Keyword(s):  
Particle Swarm Optimization ◽  
Edge Detection ◽  
Shape Matching ◽  
Particle Swarm ◽  
Ground Truth ◽  
Edge Image ◽  
Swarm Optimization ◽  
Detection Techniques ◽  
Edge Detectors ◽  
Distinct Particle

Edge detection is long-established in computer perception approach such as object detection, shape matching, medical image classification etc. For this reason many edge detectors like, Sobel, Robert, Prewitt, Canny etc. has been progressed to increase the effectiveness of the edge pixels. All these approaches work fine on images having minimum variation in intensity. Therefore, a new objective function based distinct particle swarm optimization (DPSO) is proposed in this paper to identify unbroken edges in an image. The conventional edge detectors such as “Canny” & computational intelligent techniques like ACO, GA and PSO are compared with proposed algorithm. Precision, Recall & F-Score is used as performance parameters for these edge detection techniques. The ground truth images are taken as reference edge images and all the edge images acquired by different edge detection systems are contrasted with reference edge image with ascertain the Precision, Recall and F-Score. The techniques are tested on 500 test images from the “BSD500” datasets. The empirical results presented by the proposed algorithm performance better than other edge detection techniques in the images. The proposed method observes edges more accurately and smoothly than other edge detection techniques such as “Canny, ACO, GA and PSO” in different images

scholarly journals Rapid Disaster Analysis based on SAR Techniques

2015 ◽  
Vol XL-3/W2 ◽  
pp. 281-288
Author(s):  
C. H. Yang ◽  
U. Soergel
Keyword(s):  
Change Detection ◽  
Color Image ◽  
Complex Case ◽  
False Alarms ◽  
The 2011 Tohoku Earthquake ◽  
Detection Techniques ◽  
Linear Feature ◽  
Difference Image ◽  
The Difference ◽  
Flooded Area

Due to all-day and all-weather capability spaceborne SAR is a valuable means for rapid mapping during and after disaster. In this paper, three change detection techniques based on SAR data are discussed: (1) initial coarse change detection, (2) flooded area detection, and (3) linear-feature change detection. The 2011 Tohoku Earthquake and Tsunami is used as case study, where earthquake and tsunami events provide a complex case for this study. In (1), pre- and post-event TerraSAR-X images are coregistered accurately to produce a false-color image. Such image provides a quick and rough overview of potential changes, which is useful for initial decision making and identifies areas worthwhile to be analysed further in more depth. In (2), the post-event TerraSAR-X image is used to extract the flooded area by morphological approaches. In (3), we are interested in detecting changes of linear shape as indicator for modified man-made objects. Morphological approaches, e.g. thresholding, simply extract pixel-based changes in the difference image. However, in this manner many irrelevant changes are highlighted, too (e.g., farming activity, speckle). In this study, Curvelet filtering is applied in the difference image not only to suppress false alarms but also to enhance the change signals of linear-feature form (e.g. buildings) in settlements. Afterwards, thresholding is conducted to extract linear-shaped changed areas. These three techniques mentioned above are designed to be simple and applicable in timely disaster analysis. They are all validated by comparing with the change map produced by Center for Satellite Based Crisis Information, DLR.

scholarly journals M7 subtype leukemic cell edge detection techniques with threshold value comparison and noise filters

2019 ◽  
Vol 13 (3) ◽  
pp. 1294
Author(s):  
A.S.A. Salam ◽  
M.N.M. Isa ◽  
M.I. Ahmad
Keyword(s):  
Edge Detection ◽  
Leukemic Cell ◽  
Threshold Value ◽  
Acute Myelocytic Leukemia ◽  
Threshold Values ◽  
Detection Techniques ◽  
Myelocytic Leukemia ◽  
Edge Detectors ◽  
Canny Edge ◽  
Noise Filters

The aim of this paper is to study and identify various threshold values for two prevalently used edge detection techniques, which are Sobel and Canny. The purpose is to determine which value gives an accurate result for identifying a leukemic cell. Moreover, evaluating suitability of edge detectors is also essential as feature extraction of cell depends greatly on image segmentation (edge detection). Firstly, an image of M7 subtype of Acute Myelocytic Leukemia (AML) is selected due to its diagnosing which were found lacking. Next, apply noise filters for the best of image quality. Thus by comparing image with no filter, median and average filters, useful information can be acquired. Each edge detectors is fixed with threshold value of 0-0.5 but for Cann edge detection the value can increase until 0.9. From the research, it is found that Canny edge with no filter and a threshold value of 0.7 gives a clearer image with less noise reduction.

Difference mode EXELFS with parallel-detection EELS

1992 ◽  
Vol 50 (2) ◽  
pp. 1262-1263
Author(s):  
Michael K. Kundmann ◽  
Ondrej L. Krivanek
Keyword(s):  
Edge Detection ◽  
Important Distinction ◽  
Edge Structure ◽  
Parallel Detection ◽  
Gain Variation ◽  
Ideal Solutions ◽  
Detector Cell ◽  
The Difference ◽  
Elemental Detection ◽  
Partial Correction

Parallel detection has greatly improved the elemental detection sensitivities attainable with EELS. An important element of this advance has been the development of differencing techniques which circumvent limitations imposed by the channel-to-channel gain variation of parallel detectors. The gain variation problem is particularly severe for detection of the subtle post-threshold structure comprising the EXELFS signal. Although correction techniques such as gain averaging or normalization can yield useful EXELFS signals, these are not ideal solutions. The former is a partial throwback to serial detection and the latter can only achieve partial correction because of detector cell inhomogeneities. We consider here the feasibility of using the difference method to efficiently and accurately measure the EXELFS signal.An important distinction between the edge-detection and EXELFS cases lies in the energy-space periodicities which comprise the two signals. Edge detection involves the near-edge structure and its well-defined, shortperiod (5-10 eV) oscillations. On the other hand, EXELFS has continuously changing long-period oscillations (∼10-100 eV).

scholarly journals A Dynamic Distance Measure of Picture Fuzzy Sets and Its Application

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 436
Author(s):  
Ruirui Zhao ◽  
Minxia Luo ◽  
Shenggang Li
Keyword(s):  
Fuzzy Sets ◽  
Distance Measure ◽  
Distance Measures ◽  
Numerical Comparison ◽  
Mathematical Tool ◽  
Practical Applications ◽  
Fuzzy Point ◽  
Point Operator ◽  
The Difference ◽  
Picture Fuzzy Sets

Picture fuzzy sets, which are the extension of intuitionistic fuzzy sets, can deal with inconsistent information better in practical applications. A distance measure is an important mathematical tool to calculate the difference degree between picture fuzzy sets. Although some distance measures of picture fuzzy sets have been constructed, there are some unreasonable and counterintuitive cases. The main reason is that the existing distance measures do not or seldom consider the refusal degree of picture fuzzy sets. In order to solve these unreasonable and counterintuitive cases, in this paper, we propose a dynamic distance measure of picture fuzzy sets based on a picture fuzzy point operator. Through a numerical comparison and multi-criteria decision-making problems, we show that the proposed distance measure is reasonable and effective.

scholarly journals Refinements of the Lower Bounds of the Jensen Functional

2011 ◽  
Vol 2011 ◽  
pp. 1-13 ◽  
Author(s):  
Iva Franjić ◽  
Sadia Khalid ◽  
Josip Pečarić
Keyword(s):  
Lower Bounds ◽  
Jensen Inequality ◽  
Left Hand ◽  
Right Hand ◽  
Special Cases ◽  
Jensen Functional ◽  
The Difference ◽  
The Right

The lower bounds of the functional defined as the difference of the right-hand and the left-hand side of the Jensen inequality are studied. Refinements of some previously known results are given by applying results from the theory of majorization. Furthermore, some interesting special cases are considered.

Combined Experimental and CFD Study of a HP Blade Multi-Pass Cooling System

2009 ◽  
Author(s):  
D. Jackson ◽  
P. Ireland ◽  
B. Cheong
Keyword(s):  
Heat Transfer ◽  
Film Cooling ◽  
Cooling System ◽  
Detailed Comparison ◽  
Bulk Temperature ◽  
Internal Cooling ◽  
3 Dimensional ◽  
Turbine Cooling ◽  
Cooling Hole ◽  
The Difference

Progress in the computing power available for CFD predictions now means that full geometry, 3 dimensional predictions are now routinely used in internal cooling system design. This paper reports recent work at Rolls-Royce which has compared the flow and htc predictions in a modern HP turbine cooling system to experiments. The triple pass cooling system includes film cooling vents and inclined ribs. The high resolution heat transfer experiments show that different cooling performance features are predicted with different levels of fidelity by the CFD. The research also revealed the sensitivity of the prediction to accurate modelling of the film cooling hole discharge coefficients and a detailed comparison of the authors’ computer predictions to data available in the literature is reported. Mixed bulk temperature is frequently used in the determination of heat transfer coefficient from experimental data. The current CFD data is used to compare the mixed bulk temperature to the duct centreline temperature. The latter is measured experimentally and the effect of the difference between mixed bulk and centreline temperature is considered in detail.

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