An Advanced Image Processing Prototype for Corrosion Finding Using Image Processing

2021 ◽  
Vol 18 (4) ◽  
pp. 1251-1255
Author(s):  
M. Malathi ◽  
P. Sinthia
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Detection Method ◽  
Research Work ◽  
Threshold Value ◽  
Fundamental Operation ◽  
Colour Changes ◽  
Edge Detection Method ◽  
Edge Recognition ◽  
Segmentation Threshold

The main objective of the research work is to recognize the rust of the substance with the help of Image Processing. The recognition of the rust portion of an image is carried out by quantizing of image in matrix form. The quantization process helps to perform the fundamental operation on image and also helps to identify the desired oxidation portion of an image. The corrosion portion was identified through the threshold operation, edge detection and segmentation. Threshold value assists to describe the types of the rust. Further the abrupt modification of colour in the images was captured by the edge detection method. Consequently partitioning of an image find the colour changes in the oxidized image. The corrosion portion was recognized by combining the edge recognition and partitioning process. Finally recommended methods provide the 98% accuracy to detect the rust.

scholarly journals New Edge Detection Method for Indonesian Batik

2011 ◽  
Vol 2 (1) ◽  
Author(s):  
Thomas Adi Purnomo Shidi ◽  
Suyoto Suyoto
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Edge Detection ◽  
Detection Method ◽  
New Method ◽  
Analysis Method ◽  
Unique Pattern ◽  
Detection Analysis ◽  
Edge Detection Method

Abstrak. Metode Baru Deteksi Tepi untuk Batik Indonesia. Didalam paper ini, diusulkan sebuah metode pendeteksi baru untuk motif batik. Deteksi tepi sudah sangat sering digunakan didalam pemrosesan gambar. Batik motif adalah salah satu contoh gambar yang memiliki bentuk yang unik dan menarik untuk dianalisis. Metode yang digunakan pada paper ini adalam metode canny dan prewit dan akan menghasilkan metode baru yaitu metode Thomas. Perbedaan antara metode dan hasil akan dilihat dari sisi ketepatan, qualitas hasil dan kejelasan. Contoh batik yang akan digunakan adalah motif parang, motife lereng dan udan liris. Ketiga batik tersebut memiliki pola  yang unik. Kata kunci : Canny, Prewitt, Thomas, Batik, Parang, Lereng, Udan liris. Abstract. New Edge Detection Method for Indonesian Batik. In this paper, we propose a new edge detection analysis method on batiks motif. Edge detection has been oftenly  used in computer vision and image processing. Indonesian  Batiks motif are some example of graphic picture that has unique pattern that interesting to analyse. The method that used for example on this paper are canny and prewit and produce a new method, thomas method. the different  amongs the method, the result of comparison appears on quality, accuracy and clarity. The example that we use are parang batiks motive, lereng batiks motive, and udan liris batiks motive. Three of batiks motive above are have unique pattern. Keywords: Canny, Prewitt, Thomas, Batik, Parang, Lereng, Udan liris.

Application of Image Processing in Plasma Jet Morphological Analysis

2012 ◽  
Vol 229-231 ◽  
pp. 1136-1139 ◽  
Author(s):  
Xiao Jing Tian ◽  
Hua Jun Dong ◽  
Da Peng Yin ◽  
Zi Yu Zhao
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Morphological Analysis ◽  
Detection Method ◽  
Plasma Jet ◽  
Improved Method ◽  
Forming Quality ◽  
Sobel Operator ◽  
Image Morphology ◽  
Edge Detection Method

The morphology of plasma jet (PJ) directly demonstrates whether the procedure of spray processes is stable. The paper proposes an acquisition system of PJ images and an improved edge detection method is presented to get the morphology of PJ. Firstly, the PJ images are gray enhanced to remove the influence of noises. Then they are enhanced with edge sharpening. At last, they are edge detected through Canny, Laplacian and Sobel operator. From the results we can see that the improved method can get more clear and more complete PJ image morphology than traditional one. The processing methods provide foundation for the online detection of PJ morphology and for diagnosing the forming quality.

scholarly journals Comparative Analysis of Image Quality Values on Edge Detection Methods

2020 ◽  
Vol 4 (2) ◽  
pp. 345-351
Author(s):  
Wicaksono Yuli Sulistyo ◽  
Imam Riadi ◽  
Anton Yudhana
Keyword(s):  
Image Processing ◽  
Comparative Analysis ◽  
Edge Detection ◽  
Computer Technology ◽  
Detection Method ◽  
Detection Methods ◽  
Sobel Operator ◽  
Image Edge Detection ◽  
Image Edge ◽  
Edge Detection Method

Identification of object boundaries in a digital image is developing rapidly in line with advances in computer technology for image processing. Edge detection becomes important because humans in recognizing the object of an image will pay attention to the edges contained in the image. Edge detection of an image is done because the edge of the object in the image contains very important information, the information obtained can be either size or shape. The edge detection method used in this study is Sobel operator, Prewitt operator, Laplace operator, Laplacian of Gaussian (LoG) operator and Kirsch operator which are compared and analyzed in the five methods. The results of the comparison show that the clear margins are the Sobel, Prewitt and Kirsch operators, with PSNR calculations that produce values ​​above 30 dB. Laplace and LoG operators only have an average PSNR value below 30 dB. Other quality comparisons use the histogram value and the contrast value with the highest value results in the Laplace and LoG operators with an average histogram value of 110 and a contrast value of 24. The lowest histogram and contrast value are owned by the Sobel and Prewitt operators.  

scholarly journals Fuzzy Logic based Edge Detection Method for Image Processing

2018 ◽  
Vol 8 (3) ◽  
pp. 1863 ◽  
Author(s):  
Abdulrahman Moffaq Alawad ◽  
Farah Diyana Abdul Rahman ◽  
Othman O. Khalifa ◽  
Norun Abdul Malek
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Detection Method ◽  
Detection Task ◽  
Fuzzy Logic Method ◽  
Recognition Systems ◽  
Edge Detection Method ◽  
Depth Curves

Edge detection is the first step in image recognition systems in a digital image processing. An effective way to resolve many information from an image such depth, curves and its surface is by analyzing its edges, because that can elucidate these characteristic when color, texture, shade or light changes slightly. Thiscan lead to misconception image or vision as it based on faulty method. This work presentsa new fuzzy logic method with an implemention. The objective of this method is to improve the edge detection task. The results are comparable to similar techniques in particular for medical images because it does not take the uncertain part into its account.

scholarly journals New Edge Detection Method Using Elisabeth Method: Case Study Javanese Batiks

2010 ◽  
Vol 1 (1) ◽  
Author(s):  
Elisabeth Denis Setiani ◽  
Suyoto Suyoto
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Detection Method ◽  
New Method ◽  
Unique Pattern ◽  
Low Level ◽  
Edge Detection Method

Abstract. This article will introduce a new edge detection method called Elisabeth method to analyze image. The case study here is Javanese Batik’s motif. Edges are basic low level primitives for image processing. It helps to identify pictures. Methods used are the combination between Sobel and Prewitt. This method is completely new to analyze Javanese Batik’s motif. Every batik motif has unique pattern. The purpose of this research is to improving edge detection method that already known now. The result is a new method in edge detection problems. Batik is one of the Indonesian Heritage that avowed as a Heritage World Cultures. With this research it hoped can help our country to classify and identify Batik’s motif items in Indonesia. Keywords: Prewitt, Sobel, Elisabeth, Javanese Batik, Parang, Kawung Abstrak. Metode Baru Deteksi Tepi Menggunakan Metode Elisabeth: Studi Kasus Batik Jawa. Artikel ini akan memperkenalkan sebuah metode baru deteksi tepi yang disebut dengan metode Elisabeth untuk menganalisis citra. Studi kasus yang digunakan disini adalah motif Batik Jawa. Tepi adalah primitif level dasar untuk pemrosesan citra. Ini membantu mengidentifikasi gambar. Metode yang digunakan adalah kombinasi antara Sobel dan Prewitt. Metode ini benar-benar baru untuk menganalisis motif Batik Jawa. Setiap motif batik memiliki pola yang unik. Tujuan dari penelitian ini adalah untuk meningkatkan metode deteksi tepi yang sudah dikenal sekarang. Hasilnya adalah metode baru dalam masalah deteksi tepi. Batik adalah salah satu Warisan Indonesia yang diakui sebagai Warisan Budaya Dunia. Dengan penelitian ini diharapkan dapat membantu negara kita untuk mengklasifikasikan dan mengidentifikasi motif Batik di Indonesia. Kata Kunci: Prewitt, Sobel, Elisabeth, Batik Jawa, Parang, Kawung

A Sub-Pixel Edge Detection Method Combining the Interpolation with the Moment Theory

2013 ◽  
Vol 475-476 ◽  
pp. 351-354
Author(s):  
Ya Zhou Zhou ◽  
Qiu Cheng Sun ◽  
Hao Chen
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Detection Method ◽  
Detection Accuracy ◽  
Gray Level ◽  
Two Dimensional ◽  
Moment Theory ◽  
One Dimensional ◽  
Edge Detection Method ◽  
The Moment

A new sub-pixel edge detection method is proposed to improve the detection accuracy. Firstly, using the theory of interpolation to acquire the continuous gray level distribution in one-dimensional .Therefore, the location of edge is determined. Secondly, in view of the two-dimensional edge detection, the moment spatial is taken into account. At last, the two-dimensional edge detection simplified as one-dimensional. From the test ,its known that the accuracy of the this algorithm is higher, especially for images with noise. So, the proposed algorithm has good applicability in image processing.

Research on Image Processing Method of Train Wheel

2014 ◽  
Vol 487 ◽  
pp. 699-701
Author(s):  
Fang Li ◽  
Wan Tao Li
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Digital Image ◽  
Detection Method ◽  
Processing Method ◽  
Wheel Surface ◽  
Filtering Method ◽  
Edge Detection Method ◽  
Detection Speed

In order to improve the detection precision and speed of train wheel image,it is necessary to research digital image processing technology.In this paper,a kind of appropriate image filtering method,combination of smoothing and sharpening,and a kind of appropriate edge detection method,combination directly and by column in binarization,were introduced.A clear image of wheel surface can be obtained.The method of detection of scratch was designed.Non-contact measurement of train wheel surface quality can be realized,it will lead to the detection speed is faster, accuracy is higher.

scholarly journals PERANCANGAN SISTEM SORTING BUAH JERUK MANIS BERBASIS PERBEDAAN WARNA KULIT BUAH

Heuristic ◽  
2016 ◽  
Vol 12 (02) ◽  
Author(s):  
Edi Kurniawan
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Digital Image ◽  
Detection Method ◽  
Citrus Fruit ◽  
Citrus Fruits ◽  
Maturity Level ◽  
Edge Detection Method ◽  
Orange Color

Almost all farmers use manual way to identify the level of maturity of oranges in doing the sorting. Identifying using the manual method has some drawbacks, namely the level of accuracy and farmers have already experience. With advances in technology now, sort of citrus fruits is based on the level of maturity can be done using digital image processing. Many digital image processing method one of them is the edge detection method. Edge detection method is used to determine the borders of an object. This study uses edge detection method to determine the extent of the orange color of the peel of citrus fruits because one of the characteristics of citrus fruit maturity level is how dominate the area of orange color on its peel. The results showed that with 10 oranges with a different maturity level, the system can determine it exactly. The average time required by the system to determine the level of maturity of citrus fruits is 0.6 secondsKeywords : citrus maturity, digital image processing, edge detection

An Edge Detection Approach for Fractal Image Processing

2020 ◽  
pp. 1-22
Author(s):  
Kalyan Kumar Jena ◽  
Sasmita Mishra ◽  
Sarojananda Mishra
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Detection Method ◽  
Challenging Problem ◽  
Gray Scale ◽  
Fractal Image ◽  
Detection Approach ◽  
Fractal Images ◽  
Morphological Operator ◽  
Edge Detection Method

Research in the field of fractal image processing (FIP) has increased in the current era. Edge detection of fractal images can be considered as an important domain of research in FIP. Detecting edges in different fractal images accurate manner is a challenging problem in FIP. Several methods have introduced by different researchers to detect the edges of images. However, no method works suitably under all conditions. In this chapter, an edge detection method is proposed to detect the edges of gray scale and color fractal images. This method focuses on the quantitative combination of Canny, LoG, and Sobel (CLS) edge detection operators. The output of the proposed method is produced using matrix laboratory (MATLAB) R2015b and compared with the edge detection operators such as Sobel, Prewitt, Roberts, LoG, Canny, and mathematical morphological operator. The experimental outputs show that the proposed method performs better as compared to other traditional methods.

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