Clustering Data Using Techniques of Image Processing Erode and Dilate to Avoid the Use of Euclidean Distance

2020 ◽  
pp. 187-203
Author(s):  
Noé Ortega-Sánchez ◽  
Erik Cuevas ◽  
Marco A. Pérez ◽  
Valentín Osuna-Enciso
Keyword(s):  
Image Processing ◽  
Euclidean Distance ◽  
Clustering Data

scholarly journals Quality Improvement for Exemplar-based Image Inpainting using a Modified Searching Mechanism

2020 ◽  
Vol 4 (1) ◽  
pp. 1
Author(s):  
Mariwan Wahid Ahmed ◽  
Alan Anwer Abdulla
Keyword(s):  
Image Processing ◽  
Image Compression ◽  
Euclidean Distance ◽  
Image Inpainting ◽  
Input Image ◽  
Second Step ◽  
Research Areas ◽  
Potential Applications ◽  
Priority Function ◽  
Popular Images

Digital image processing has a significant impact in different research areas including medical image processing, biometrics, image inpainting, object detection, information hiding, and image compression. Image inpainting is a science of reconstructing damaged parts of digital images and filling-in regions in which information are missing which has many potential applications such as repairing scratched images, removing unwanted objects, filling missing area, and repairing old images. In this paper, an image inpainting algorithm is developed based on exemplar, which is one of the most important and popular images inpainting technique, to fill-in missing area that caused either by removing unwanted objects, by image compression, by scratching image, or by image transformation through internet. In general, image inpainting consists of two main steps: The first one is the priority function. In this step, the algorithm decides to select which patch has the highest priority to be filled at the first. The second step is the searching mechanism to find the most similar patch to the selected highest priority patch to be inpainted. This paper concerns the second step and an improved searching mechanism is proposed to select the most similar patch. The proposed approach entails three steps: (1) Euclidean distance is used to find the similarity between the highest priority patches which need to be inpainted with each patch of the input image, (2) the position/location distance between those two patches is calculated, and (3) the resulted value from the first step is summed with the resulted value obtained from the second step. These steps are repeated until the last patch from the input image is checked. Finally, the smallest distance value obtained in step 3 is selected as the most similar patch. Experimental results demonstrated that the proposed approach gained a higher quality in terms of both objectives and subjective compared to other existing algorithms.

scholarly journals PRINTING DEFECT IDENTIFICATION IN PHARMACEUTICAL BLISTERS USING IMAGE PROCESSING

2018 ◽  
Vol 11 (3) ◽  
pp. 210 ◽  
Author(s):  
Durga Karthik ◽  
Vijayarekha K ◽  
Arun Ar
Keyword(s):  
Image Processing ◽  
Chemical Composition ◽  
Euclidean Distance ◽  
Distance Method ◽  
Defect Identification ◽  
Pharmaceutical Tablets ◽  
Manufacturing Line ◽  
Manufacturing Location ◽  
Image Processing Algorithms ◽  
Processing Algorithms

 Objective: Our aim is to detect printing defects in pharmaceutical tablets from the manufacturing line using image processing techniques.Methods: The printed labels contain the details of the chemical composition, date of manufacture, date of expiry, manufacturing location, etc., images of the labels are obtained and processed using image processing algorithms to detect any defects on the labels before dispatch.Results: The printing defects on the labels such as missing letters, words, lines, and disorientation of alignments.Conclusion: Euclidean distance method was used for comparison that yielded 95% accuracy in removing tablets with printing defects.

Edge Detection Algorithm for Surface Image Based on Euclidean Distance Discriminant

2012 ◽  
Vol 459 ◽  
pp. 347-350 ◽  
Author(s):  
Gang Li ◽  
Zi Qiang Li ◽  
Ya La Tong
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Euclidean Distance ◽  
Detection Algorithm ◽  
Target Information ◽  
Edge Detection Algorithm ◽  
Background Interference ◽  
Surface Image

For the problem of difficult to detect the edge in the surface image processing, we used the Euclidean distance from the selected pixels in the corner of the neighborhood window to the centre point of that to measure the extent of being edge, and then search for suitable threshold to extract the expected edge pixels. This algorithm can extract target information better, while also inhibiting the background interference, and it is a good algorithm which is worthy of further exploration

A Flame Fringe Detection Algorithm Based on Mahalanobis Distance

2013 ◽  
Vol 722 ◽  
pp. 467-471
Author(s):  
Zhen Chen ◽  
Ji Hong Shen
Keyword(s):  
Image Processing ◽  
Mahalanobis Distance ◽  
Euclidean Distance ◽  
Simulation Analysis ◽  
Detection Algorithm ◽  
High Accuracy ◽  
Fire Disaster ◽  
Flame Detection ◽  
Image Morphology ◽  
Single Pixel

In this paper, a mahalanobis distance based flame fringe detection algorithm through digital image processing was proposed according to the insufficient accuracy and excessive interference of the traditional flame fringe detection algorithm. The similarity between the pixels in GRB image and the sample flame pixels was first calculated through Euclidean distance and mahalanobis distance for classifying the pixels in the image and finishing flame segmentation, and then the image was processed through binarization, and finally flame fringe was extracted through gradient method and image morphology. Also, a simulation analysis was made, and the results showed that the fringe extracted with this algorithm was single-pixel, smooth and continuous without cross, had less interference, and possessed high accuracy and reliability. Thus, this method can meet the flame detection in the complex images such as fire disaster image.

scholarly journals IDENTIFICATION OF VARIOUS DEFECTS IN PHARMACEUTICAL TABLETS USING IMAGE PROCESSING TECHNIQUES

2017 ◽  
Vol 10 (11) ◽  
pp. 106 ◽  
Author(s):  
Durga Karthik ◽  
Vijayarekha K ◽  
Saranya S
Keyword(s):  
Image Processing ◽  
Euclidean Distance ◽  
Color Variation ◽  
Pharmaceutical Tablets ◽  
Image Processing Techniques ◽  
Manufacturing Line ◽  
Similarity Measuring ◽  
Processing Techniques

  Objective: Our aim is to identify the damaged tablets from the manufacturing line using image processing techniques and remove them before packaging.Methods: The various problems posed during inspection are broken tablets, corner chips, black or other color spots in tablets, empty blisters (without one or more tablets or capsules), foreign particles/color variation in the tablets/capsules, improper sealing, etc., Image processing techniques will be used for defect detection.Results: Tablets are available in packed forms that are usually transparent, semi-transparent or opaque. Euclidean distance was employed for detecting defects, during testing that had a similarity of 100 for tablets with no defects, for defective blisters had similarity ranging from 98 to 41. Empty blisters had a similarity of 0 on comparing with trained images.Conclusion: Similarity measuring based technique can accurately detect defects in the pharmaceutical tablets, hence can be adopted for removing such blisters from the manufacturing line itself.

Research on Methods of Tire Sensory Measurement Based on Image Processing

2011 ◽  
Vol 230-232 ◽  
pp. 900-904 ◽  
Author(s):  
Rong Bao Chen ◽  
Jing Tao ◽  
Wu Ting Fan ◽  
Jun Jie Zhang
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Euclidean Distance ◽  
Traffic Accidents ◽  
Pressure Overload ◽  
Texture Features ◽  
Tire Pressure ◽  
Distance Method ◽  
Proportion Method

This paper proposes and analyzes sensory measurement of tire based on image processing, which uses tangent value method, proportion method and Euclidean distance method to detect tire pressure and overload and uses Tamura texture features to describe tire abrasion level. The research presents a contactless way to detect tire pressure, overload and abrasion level and has certain advantages and innovations in function and implementation compared with existing TPMS which can’t detect the tire abrasion level. This research is an application of image processing-based computer vision in tire sensory measurement; it makes the measurement of tire automatically and intelligently and can be used to prevent traffic accidents caused by tires effectively. There are practical values.

scholarly journals Identifikasi Tulisan Tangan Huruf Katakana Jepang Dengan Metode Euclidean

2020 ◽  
Vol 4 (1) ◽  
pp. 29
Author(s):  
Imam Riadi ◽  
Abdul Fadlil ◽  
Putri Annisa
Keyword(s):  
Image Processing ◽  
Feature Extraction ◽  
Learning Process ◽  
Euclidean Distance ◽  
Image Data ◽  
Gray Level ◽  
Accuracy Rate ◽  
Distance Method ◽  
Object A ◽  
Data Acquisition Process

Katakana is one of the traditional Japanese letters used to absorption words from other languanges. In the inttroduction of an object a learning process is needed, which is obtained through the characteristics and experience of observing similar objects after being acquired. But manually it is quite difficult to distinguish between 5 hiragana vowels starting from the image data acquisition process, image processing, feature extraction using Gray Level Co-occurance Matrix (GLCM) while classifiers use the euclidean distance method. The results of the tests carried out showed an accuracy rate of around 78% using the euclidean method.

scholarly journals A Generalized Squared Euclidean Distance Transform with Voronoi Maps

2006 ◽  
Author(s):  
Benjamin King ◽  
Rolf Döker ◽  
Simone Meier ◽  
Hoen-oh Shin ◽  
Michael Galanski
Keyword(s):  
Image Processing ◽  
Euclidean Distance ◽  
Euclidean Ball ◽  
Distance Transform ◽  
Euclidean Metric ◽  
Euclidean Distance Transform ◽  
Standard Distance ◽  
Squared Euclidean Distance

This document describes the implementation of an algorithm that computes a generalization of the distance transform with the squared euclidean metric.The generalization allows for interesting image operators, e.g. a morphologic dilation with euclidean ball structure elements that can vary in size across the image. Voronoi maps and the standard distance transform can be computed as well.The algorithm is provided as an image processing filter for ITK. Several example programs demonstrate its applications.

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