scholarly journals Detection of Fake Currency using Image Processing

2021 ◽  
Vol 9 (VII) ◽  
pp. 419-423
Author(s):  
Ashik Shiby
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Programming Language ◽  
Money Laundering ◽  
National Currency ◽  
Ordinary People ◽  
Research Project ◽  
Legal Entity ◽  
Grey Scale ◽  
Image Separation

In its definition, the term 'currency' defines an agreed-upon exchange item, the national currency being the legal entity used by the selected controlling entity. Throughout history, issuers have faced 1 common threat: counterfeit. In recent years fake money note has been printed that has resulted in significant losses and damage to society. Therefore, it becomes necessary to build a tool for earning money. This research project proposes a way to look at the note of counterfeit money distributed in our country through their image. After selecting an image use pre-processing. In pre-processing, the acquired image is cropped, smooth, and adjust. Change the image to grey-scale. After conversion use image separation. Features are extracted and reduce. Finally, compare the picture to be real or fake. Duplicate money has been a major problem in the market. There are currency counting machines available in banks and other trading venues to check financial authenticity. Most people do not have access to such programs which is why there is a need for fake money laundering software, which can be used by ordinary people. This proposed framework uses Image Processing to determine whether the money is real or counterfeit. The research project program is built entirely using Python's programming language. It has the methods such as grayscale conversion, edge detection, segmentation, etc.

scholarly journals Fractional-Order Colour Image Processing

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 457
Author(s):  
Manuel Henriques ◽  
Duarte Valério ◽  
Paulo Gordo ◽  
Rui Melicio
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Fractional Derivative ◽  
Fractional Order ◽  
Fractional Derivatives ◽  
Grey Scale ◽  
Colour Image ◽  
Colour Image Processing ◽  
Image Processing Algorithms ◽  
Processing Algorithms

Many image processing algorithms make use of derivatives. In such cases, fractional derivatives allow an extra degree of freedom, which can be used to obtain better results in applications such as edge detection. Published literature concentrates on grey-scale images; in this paper, algorithms of six fractional detectors for colour images are implemented, and their performance is illustrated. The algorithms are: Canny, Sobel, Roberts, Laplacian of Gaussian, CRONE, and fractional derivative.

The Use of Hybrid Technique: Thresholding and Edge Detection for Identifying River from Aerial Photo

2012 ◽  
Author(s):  
Mohd. Shafry Mohd. Rahim ◽  
Nik Isrozaidi Nik Ismail ◽  
Mohd. Azuan Shah Idris
Keyword(s):  
Image Processing ◽  
Feature Extraction ◽  
Edge Detection ◽  
Key Words ◽  
Detection Technique ◽  
Hybrid Technique ◽  
Aerial Photo ◽  
Hybrid Techniques ◽  
Grey Scale ◽  
Sobel Edge Detection

Bidang pemprosesan imej merupakan satu bidang yang luas dengan pelbagai aplikasi terutama dalam bidang sains dan industri. Pemprosesan imej digunakan dalam manipulasi dan penambahbaikan imej untuk memudahkan proses seterusnya. Penyelidikan ini melibatkan penggunaan teknik hybrid yang menggabungkan teknik threshold dan teknik pengesanan sisi Sobel, untuk mengenal pasti sungai daripada imej berskala kelabu. Teknik thresholding digunakan untuk mengurangkan piksel sisi yang tak maksima, piksel sisi yang lemah dan mengurangkan kesan hingar, manakala edge detection digunakan untuk mengesan kehadiran piksel sisi. Hasil yang diperolehi daripada penggunaan teknik hybrid dibandingkan dengan teknik–teknik yang sedia ada seperti Sobel, Prewitt, Laplacian dan Robert Cross. Kata kunci: Pemprosesan imej, mengenal pasti ciri-ciri, pengesanan garis, foto udara The field of image processing is a broad field with many applications in science and industry. Image processing is used to manipulate and enhance an image, which ease the next process. This research involves the use of a hybrid techniques, which is a combination of thresholding and Sobel edge detection technique, to recognize a river from a grey scale image. Thresholding technique is used to reduce non-maxima pixels, weak edges and noise, whilst the edge detection technique is used to detect location of the edges. The output from this hybrid technique is compared to the existing techniques such as Sobel, Prewitt, Laplacian, and Robert Cross technique. Key words: Image processing, feature extraction, edge detection, aerial photo

scholarly journals Machine Learning-Based Technique for Image Classification and Identification of Similarity for Commonness of Source

2020 ◽  
Vol 9 (6) ◽  
pp. 544-548
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Edge Detection ◽  
Image Classification ◽  
Programming Language ◽  
Python Programming Language ◽  
Reserve Bank ◽  
Python Programming ◽  
Highlight Extraction ◽  
Reserve Bank Of India

In India Every year RBI (Reserve bank of India) faces the issue of fake currency. Fake Currency has consistently been an issue that has made a lot of chaos in the market. The expanding mechanical progressions have made the opportunities for making progressively fake currency which is circled in the market which decreases the general economy of the nation. There are machines present at banks and other business regions to check the validness of the monetary forms. Be that as it may, a typical man doesn't approach such frameworks and henceforth a requirement for a product to distinguish counterfeit cash emerges, which can be utilized by average folks. This proposed framework utilizes Image Processing to identify whether the currency is real or fake. The framework is structured utilizing Python programming language and OpenCV. It comprises of the means, for example, grayscale detection, edge detection, Highlight Extraction, and so forth which are performed utilizing reasonable strategies. And which will be further implemented in the Framework for Classification and Identification of Similarity for Commonness of Source

scholarly journals System for Fake Currency Detection Using Image Processing

2022 ◽  
Vol 10 (1) ◽  
pp. 349-352
Author(s):  
Prof. F. S. Ghodichor
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Global Economy ◽  
Ordinary People ◽  
Python Programming Language ◽  
Technological Growth ◽  
Average Person ◽  
Growth Development ◽  
Python Programming ◽  
To Receive

Abstract: Counterfeit money has always existed an issue that has caused many problems in the market. Technological growth development has made it possible to create extra counterfeit items which are distributed in the mitigation market the global economy. Bangui existing banking equipment and so on trading sites to check the authenticity of funds. But the average person does not do that have access to such systems and that is why they are needed in order for the software to receive counterfeit money, which can be used by ordinary people. This the proposed system uses image processing to find out if the money is real or fake. System built uses the Python system completely language. It contains similar steps grayscale modification, edge detection, separation, etc. made using appropriate methods. Keyword: Counterfeit currency, Image Processing, Python programming language, grayscale conversion, edge detection, segmentation.

scholarly journals Implementation of Sobel Method Based Edge Detection for Flower Image Segmentation

SinkrOn ◽  
2019 ◽  
Vol 3 (2) ◽  
pp. 161
Author(s):  
Asmaidi Asmaidi ◽  
Darma Setiawan Putra ◽  
Muharratul Mina Risky ◽  
Fitria Ulfa R
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Programming Language ◽  
Image Data ◽  
Input Image ◽  
Interactive System ◽  
Boundary Line ◽  
Pixel Value

Edge detection is the first step to cover information in the image. The edges characterize the boundaries of objects and therefore edges are useful for the process of segmentation and identification in the image. The purpose of edge detection is to increase the appearance of the boundary line of the object in the image. The sobel method is a method that uses two kernels measuring 3x3 pixels for gradient calculations so that the estimate gradient is right in the middle of the window. Digital image processing aims to manipulate image data and analyze an image with the help of a computer. Matlab is made to facilitate the use of two collections of subroutines in the fortran library, linpack and eispack, in handling matrix computing, and develops into an interactive system as a programming language. Experimental results from the input image research, namely the flower image have different MSE values because each input image has a different pixel value

Algorithms for segmentation and recognition of objects on medical images based on chiarlet transformation and neural networks

2020 ◽  
pp. 35-45
Author(s):  
Y.A. Hamad ◽  
K.V. Simonov ◽  
A.S. Kents
Keyword(s):  
Neural Networks ◽  
Image Processing ◽  
Computer Vision ◽  
Edge Detection ◽  
Medical Images ◽  
Classification Algorithms ◽  
Visual Data ◽  
Recognition Of Objects

The paper considers general approaches to image processing, analysis of visual data and computer vision. The main methods for detecting features and edges associated with these approaches are presented. A brief description of modern edge detection and classification algorithms suitable for isolating and characterizing the type of pathology in the lungs in medical images is also given.

Digital Image Processing for Detecting and Classifying Plant Diseases

2017 ◽  
Vol 2 (11) ◽  
pp. 1-7
Author(s):  
Izay A. ◽  
Onyejegbu L. N.
Keyword(s):  
Image Processing ◽  
Fuzzy Logic ◽  
Programming Language ◽  
Design Methodology ◽  
Fuzzy Logic Controller ◽  
Object Oriented ◽  
Plant Diseases ◽  
Analysis And Design ◽  
Crop Diseases ◽  
Growing Population

Agriculture is the backbone of human sustenance in this world. With growing population, there is need for increased productivity in agriculture to be able to meet the demands. Diseases can occur on any part of a plant, but in this paper only the symptoms in the fruits of a plant is considered using segmentation algorithm and edge/ sizing detectors. We also looked at image processing using fuzzy logic controller. The system was designed using object oriented analysis and design methodology. It was implemented using MySQL for the database, and PHP programming language. This system will be of great benefit to farmers and will encourage them in investing their resources since crop diseases can be detected and eliminated early.

scholarly journals Fractional Order Processing of Satellite Images

2021 ◽  
Vol 11 (11) ◽  
pp. 5288
Author(s):  
Manuel Henriques ◽  
Duarte Valério ◽  
Rui Melicio
Keyword(s):  
Edge Detection ◽  
Fractional Order ◽  
High Performance ◽  
Satellite Images ◽  
Automatic Detection ◽  
Automatic Processing ◽  
Order Processing ◽  
Detection Algorithms ◽  
Grey Scale ◽  
Fixed Set

Nowadays, satellite images are used in many applications, and their automatic processing is vital. Conventional integer grey-scale edge detection algorithms are often used for this. This study shows that the use of color-based, fractional order edge detection may enhance the results obtained using conventional techniques in satellite images. It also shows that it is possible to find a fixed set of parameters, allowing automatic detection while maintaining high performance.

IMAGE PROCESSING VIA CNN GENES WITH VON NEUMANN NEIGHBORHOODS

2005 ◽  
Vol 15 (12) ◽  
pp. 3999-4006 ◽  
Author(s):  
FENG-JUAN CHEN ◽  
FANG-YUE CHEN ◽  
GUO-LONG HE
Keyword(s):  
Image Processing ◽  
Computer Simulation ◽  
Edge Detection ◽  
Vertical Line ◽  
Corner Detection ◽  
Line Detection ◽  
Von Neumann ◽  
Center Point ◽  
Better Than

Some image processing research are restudied via CNN genes with five variables, and this include edge detection, corner detection, center point extraction and horizontal-vertical line detection. Although they were implemented with nine variables, the results of computer simulation show that the effect with five variables is identical to or better than that with nine variables.

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