Industrial Flame Edge Detection Algorithm Based on Gray Dominant Filter

Zhenhua Wei,Jianqiang Qiao 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.2

Industrial furnace flame detection is directly related to the safety and economic operation of boiler. The flame edge detection is one of the most key parts of the flame detection. At present, there are many edge detection algorithms for normal object but few for industrial flame edge detection which cannot provide fully support for furnace flame combustion stability, flame 3D reconstruction and flame temperature field reconstruction. One new industrial flame image edge detection algorithm based on industrial flame image characteristics is proposed in this paper. This algorithm can effectively remove noise level in flame image and well maintain flame image edge features, compute the gradients from multiple-directions for entirely detecting flame edge information. Moreover, this algorithm is verified by experiment in this paper to present high performance in resisting noise, and clearly see continuous flame edge curve, which reveals better effect in industrial flame edge detection than other edge detection algorithms.

Comparison of Various Edge Detection Technique

Sujeet Das 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.2

Edge is the basic feature of image. Edges form the outline of an object. The need of edge detection is to find the discontinuities in depth, discontinuities in surface orientation, changes in material properties and variations in scene illumination. So edge detection is one of the most commonly used operations in image analysis and there are probably more algorithm for detecting edges. In this paper various edge detectors like Canny, Sobel, Roberts and Prewitt are compared. These operators are more susceptible to noise and do not give satisfactory result for face outline. For overcoming this disadvantage morphological method is studied and the result of edge detection using morphological method is compared with Canny edge detector, Sobel edge detector, Roberts edge detector and Prewitt edge detector.Wood and Glass Images are taken up as a special conditions for wider number of applications.

Canny Optimization Algorithm Based on Improved Anisotropic Diffusion Function Filtering

Zhang Xianhong,Zhang Chunrui 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.7

Image edge detection is an important part of image processing, and the effect of edge detection is also directly affected by image analysis, recognition and understanding. Canny operator is the most commonly used image edge detection operator. However, this operator has some limitations. The traditional Canny operator uses Gaussian filtering which may bring problems such as missing edge information and false edge. Besides, the selection of high and low thresholds of the traditional Canny operator are not accurate, and cannot be carried out by self-adaption. In order to solve these problems, this paper presents an optimized algorithm for Canny operator. In this paper, an improved anisotropic diffusion function is used to filter the image, and the improved filtering not only reduces the noise, but also maintains the edge information of the image. Additionally, this paper has improved the maximum between-class variance method (OTSU) to select the high and low thresholds of Canny operator by self-adaption. The improved algorithm is applied to edge detection of various images, and the results indicated that the improved Canny operator is effective in reducing noise and extracting edge.

Development of an Edge-Based Algorithm for Moving-Object Detection Using Background Modeling

Shin, Won-Yong,Kabir, M. Humayun,Hoque, M. Robiul,Yang, Sung-Hyun The Korea Institute of Information and Commucation 2014 Journal of information and communication convergen Vol.12 No.3

Edges are a robust feature for object detection. In this paper, we present an edge-based background modeling method for the detection of moving objects. The edges in the image frames were mapped using robust Canny edge detector. Two edge maps were created and combined to calculate the ultimate moving-edge map. By selecting all the edge pixels of the current frame above the defined threshold of the ultimate moving edges, a temporary background-edge map was created. If the frequencies of the temporary background edge pixels for several frames were above the threshold, then those edge pixels were treated as background edge pixels. We conducted a performance comparison with previous works. The existing edge-based moving-object detection algorithms pose some difficulty due to the changes in background motion, object shape, illumination variation, and noises. The result of the performance evaluation shows that the proposed algorithm can detect moving objects efficiently in real-world scenarios.

잡음 영상에서의 에지 검출

구윤모,김영로 (사)디지털산업정보학회 2012 디지털산업정보학회논문지 Vol.8 No.3

In this paper, we propose a method of edge detection for noisy image. The proposed method uses a progressive filter for noise reduction and a Sobel operator for edge detection. The progressive filter combines a median filter and a modified rational filter. The proposed method for noise reduction adjusts rational filter direction according to an edge in the image which is obtained by median filtering. Our method effectively attenuates the noise while preserving the image details. Edge detection is performed by a Sobel operator. This operator can be implemented by integer operation and is therefore relatively fast. Our proposed method not only preserves edge, but also reduces noise in uniform region. Thus, edge detection is well performed. Our proposed method could improve results using further developed Sobel operator. Experimental results show that our proposed method has better edge detection with correct positions than those by existing median and rational filtering methods for noisy image.

Scrolling text detection based on region characteristic analysis for frame rate up-conversion

Lee, Ho Sub,Kang, Suk-Ju,Kim, Young Hwan Elsevier 2018 Displays Vol.55 No.-

<P><B>Abstract</B></P> <P>This paper proposes a new scrolling text detection method for frame rate up-conversion, which uses a text edge detector and motion vector distribution analysis of the detected text. Existing methods use either edge or motion vector information of an image for scrolling text detection. Thus, when text begins or ends scrolling at the frame boundary, they have difficulty in detecting the text. Moreover, these methods use a fixed threshold to detect text edges. This makes their detection accuracy dependent on the local characteristic of an image. To overcome these drawbacks, the proposed algorithm uses both text edge detector and motion vector distribution analysis. The proposed method consists of the following three steps. In the first step, a text map is generated by the text edge detector based on region-adaptive thresholding for luminance change. Then, an initial scrolling text map is generated by calculating the difference between the previous and current text maps. Finally, the scrolling text is refined by analyzing the region characteristic of the detected text, including density, structure, and motion vector distribution. Compared with the state-of-the-art method, the experimental results show that the proposed method increases the detection accuracy by up to 17.6%. In addition, when the proposed algorithm is used for scrolling text detection, the frame rate up-conversion algorithm can generate high quality interpolated images for the scrolling text regions.</P> <P><B>Highlights</B></P> <P> <UL> <LI> The proposed algorithm uses a region-adaptive threshold for text edge detection. </LI> <LI> It refines scrolling text regions using their text edge characteristics. </LI> <LI> It can be used for FRUC to improve MVs in the presence of scrolling texts. </LI> </UL> </P>

형태학적 연산과 경계추출 학습이 강화된 U-Net을 활용한 Sentinel-1 영상 기반 수체탐지

김휘송 ( Hwisong Kim ),김덕진 ( Duk-jin Kim ),김준우 ( Junwoo Kim ) 대한원격탐사학회 2022 大韓遠隔探査學會誌 Vol.38 No.5

실시간 범람 모니터링을 위해 인공위성 SAR영상을 활용하는 수체탐지에 대한 필요성이 대두되었다. 주야와 기상에 상관없이 주기적으로 촬영 가능한 인공위성 SAR 영상은 육지와 물의 영상학적 특징이 달라 수체탐지에 적합하나, 스페클 노이즈와 영상별 상이한 밝기 값 등의 한계를 내포하여 다양한 시기에 촬영된 영상에 일괄적으로 적용 가능한 수체탐지 알고리즘 개발이 쉽지 않다. 이를 위해 본 연구에서는 Convolutional Neural Networks (CNN)기반 모델인 U-Net 아키텍처에 레이어의 조합인 모듈을 추가하여 별도의 전처리 없이 수체탐지의 정확도 향상 방법을 제시하였다. 풀링 레이어의 조합을 활용하여 형태학적 연산처리 효과를 제공하는 Morphology Module과 전통적인 경계탐지 알고리즘의 가중치를 대입한 컨볼루션 레이어를 사용하여 경계 학습을 강화시키는 Edge-enhanced Module의 다양한 버전을 테스트하여, 최적의 모듈 구성을 도출하였다. 최적의 모듈 버전으로 판단된 min-pooling과 max-pooling이 연속으로 이어진 레이어와 min-pooling로 구성된 Morphology 모듈과 샤를(Scharr) 필터를 적용한 Edge-enhanced 모듈의 산출물을 U-Net 모델의 conv 9에 입력자료로 추가하였을 때, 정량적으로 9.81%의 F1-score 향상을 보여주었으며, 기존의 U-Net 모델이 탐지하지 못한 작은 수체와 경계선을 보다 세밀하게 탐지할 수 있는 성능을 정성적 평가를 통해 확인하였다. Synthetic Aperture Radar (SAR) is considered to be suitable for near real-time inundation monitoring. The distinctly different intensity between water and land makes it adequate for waterbody detection, but the intrinsic speckle noise and variable intensity of SAR images decrease the accuracy of waterbody detection. In this study, we suggest two modules, named ‘morphology module’ and ‘edge-enhanced module’, which are the combinations of pooling layers and convolutional layers, improving the accuracy of waterbody detection. The morphology module is composed of min-pooling layers and max-pooling layers, which shows the effect of morphological transformation. The edge-enhanced module is composed of convolution layers, which has the fixed weights of the traditional edge detection algorithm. After comparing the accuracy of various versions of each module for U-Net, we found that the optimal combination is the case that the morphology module of min-pooling and successive layers of min-pooling and max-pooling, and the edge-enhanced module of Scharr filter were the inputs of conv9. This morphologic and edge-enhanced U-Net improved the F1-score by 9.81% than the original U-Net. Qualitative inspection showed that our model has capability of detecting small-sized waterbody and detailed edge of water, which are the distinct advancement of the model presented in this research, compared to the original U-Net.

Detection of Edges in Color Images

Ganchimeg, Ganbold,Turbat, Renchin The Institute of Electronics and Information Engin 2014 IEIE Transactions on Smart Processing & Computing Vol.3 No.6

Edge detection considers the important technical details of digital image processing. Many edge detection operators already perform edge detection in digital color imaging. In this study, the edge of many real color images that represent the type of digital image was detected using a new operator in the least square approximation method, which is a type of numerical method. The Linear Fitting algorithm is computationally more expensive compared to the Canny, LoG, Sobel, Prewitt, HIS, Fuzzy, Parametric, Synthetic and Vector methods, and Robert' operators. The results showed that the new method can detect an edge in a digital color image with high efficiency compared to standard methods used for edge detection. In addition, the suggested operator is very useful for detecting the edge in a digital color image.

Edge Detection을 이용한 간 혈관 추출

서정주(Jeong-Joo Seo),박종원(Jong-Won Park) 한국컴퓨터정보학회 2012 韓國컴퓨터情報學會論文誌 Vol.17 No.3

간 혈관 구조는 간에 대한 질병을 판단하거나 간 수술 계획을 세우는 데 중요한 요소이다. 특히 생체간이식에서 간 혈관 구조는 기증자와 수혜자의 안전을 보장하기 위하여 수술 전 환자의 간 상태를 파악하고 좌우엽의 체적을 계산하는 중요한 근거로 활용된다. 본 연구는 조영제를 투여한 복부 MDCT 영상에서 추출된 간 영상으로부터 간 혈관을 자동추출하기 위하여 노이즈에 강한 Canny edge detection을 활용할 수 있는 방안을 제안한다. 환자마다 달라질 수 있는 간 영상의 밝기와는 독립적으로 간 내부의 혈관을 추출하기 위하여 간 영상의 히스토그램과 평균 픽셀값을 이용하여 Canny 알고리즘에 사용되는 최적의 파라미터들을 정의한다. 간 영상의 밝기에 따라 파라미터를 수동으로 조절하는 경우보다 시간을 절약할 수 있다. 찾아진 혈관의 경계선에서픽셀의 밝기를 이용하여 후보 혈관을 추출한다. 최종적으로 수평과 수직방향으로 연결된 혈관이나 고립된 혈관을 검색하는 시스템을 이용하여 추출에 실패한 혈관을 추가하고 노이즈를 제거한다. 그 결과로써 환자마다 나타나는 다양한 혈관 모양을 정확하게 3차원으로 재구성한다. Hepatic vessel tree is the key structure for hepatic disease diagnosis and liver surgery planning. Especially, it is used to evaluate the donors' and recipients' liver for the LDLT(Living Donors Liver Transplantation) and estimate the volumes of left and right hepatic lobes for securing their life in the LDLT. In this study, we propose a method to apply canny edge detection that is not affected by noise to the liver images for automatic segmentation of hepatic vessels tree in contrast abdominal MDCT image. Using histograms and average pixel values of the various liver CT images, optimized parameters of the Canny algorithm are determined. It is more time-efficient to use the common parameters than to change parameters manually according to CT images. Candidates of hepatic vessels are extracted by threshold filtering around the detected the vessel edge. Finally, using a system which detects the true-negatives and the false-positives in horizontal and vertical direction, the true-negatives are added in candidate of hepatic vessels and the false-positives are removed. As a result of the process, the various hepatic vessel trees of patients are accurately reconstructed in 3D.

잡음 종류와 잡음 제거방식에 따른 영상의 윤곽선 검출 비교

김지은,이덕우 한국멀티미디어학회 2023 멀티미디어학회논문지 Vol.26 No.4

In this paper, we show comparison results of edge detection of images that have additive gaussian noise or salt and pepper noise by using various techniques of noise removal such as filtering, morphology and deep learning based ones. In particular, this present work provides comparison results of noise removal by using gaussian filter, open and close operations of morphology and auto-encoder model followed by carrying out edge detection. Robert cross, Sobel, Prewitt and Canny detectors are used for edge detection of the images with noise removal. Experimental results show that noise removal results are different with characteristics of noise and techniques applied for noise removal. In addition, deep learning based technique, auto-encoder does not always shows superior results of noise removal, particularly in the case of existence of salt-pepper noise. In the experiments, gaussian noise or salt-pepper noise is used and peak signal noise ratio (PSNR) is used for quantitative comparison and the results of edge detection is qualitatively compared from visual perspective.