scholarly journals PEKEMON: A Mobile Application for Detecting Fake Money

2016 ◽  
Vol 25 (1) ◽  
Author(s):  
Roselie B. Alday ◽  
Jelyn G. Andal ◽  
Micah C. Ilagan ◽  
Niña Daniela A. Meliton ◽  
Marnely S. Mercado
Keyword(s):  
Operating System ◽  
Image Segmentation ◽  
Mobile Application ◽  
Vertical Direction ◽  
Ultra Violet ◽  
Detection Algorithm ◽  
Edge Detection Algorithm ◽  
Violet Light ◽  
Android Operating System ◽  
Sobel Edge Detection

Banko Sentral ng Pilipinas (BSP) released and redesigned/new Philippine peso bills last December 2010 in accordance to stop the proliferation of counterfeit money, but circulation of fake money continues. The project developed a mobile application that will help detect fake new Philippine bills by using an algorithm in a mobile application. The researchers devised a tool in detecting fake money by distinguishing between genuine and counterfeit Philippine peso bills using built-in phone camera. The method used in detecting fake money was image segmentation using Sobel Edge Detection Algorithm. It converted the image to grayscale and detected two kinds of edges in an image: Vertical Direction Edges and Horizontal Direction Edges. After the image was converted, it counts the number of white pixels which had been the basis to determine if it is fake or not. The mobile application is available for android operating system only. The programming language that the researchers used is Java. The application resulted to 50% - 70% accuracy in detecting fake bills because it uses a phone camera for detection instead of Ultra Violet Light. It is recommended that the design be enhanced by adding more functionality such as sending a message to the office of Banko Sentral ng Pilipinas (BSP) if the money is detected as fake.

scholarly journals Analysis of Cryptography Algorithms Implemented in Android Mobile Application

2021 ◽  
Vol 50 (4) ◽  
pp. 786-807
Author(s):  
Alen Salkanovic ◽  
Sandi Ljubic ◽  
Ljubisa Stankovic ◽  
Jonatan Lerga
Keyword(s):  
Operating System ◽  
Mobile Application ◽  
Data Encryption ◽  
Performance Outcomes ◽  
Primary Objective ◽  
Symmetric Encryption ◽  
Variable Size ◽  
Encryption Algorithms ◽  
Android Operating System ◽  
Time Required

This paper evaluates the performances of numerous encryption algorithms on mobile devices running the Android operating system. The primary objective of our research was to measure and compare the relative performances of tested algorithm implementations (Data Encryption Standard (DES), 3DES, Advanced Encryption Standard (AES), ChaCha20, Blowfish, and Rivest Cipher 4 (RC4)) on the Android platform. The algorithms were compared in terms of CPU utilization by measuring the time required to encrypt and decrypt variable size text files. Besides evaluating the six common symmetric encryption ciphers, a comparison has been conducted for several Password-Based Encryption (PBE) algorithms. Diverse cipher transformations were evaluated for each algorithm by utilizing various feedback modes and padding schemes. Two smartphone devices were used for testing, with different versions of the Android operating system and hardware specifications. The summarized performance outcomes for various cipher transformations are presented to demonstrate the effectiveness of each algorithm.

scholarly journals Hardware Implementation of Sobel Edge Detection Algorithm

2020 ◽  
Vol 32 ◽  
pp. 03051
Author(s):  
Ankita Pujare ◽  
Priyanka Sawant ◽  
Hema Sharma ◽  
Khushboo Pichhode
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Feature Detection ◽  
Hardware Implementation ◽  
Software Tool ◽  
Detection Algorithm ◽  
Edge Detection Algorithm ◽  
Detection Algorithms ◽  
Sobel Edge Detection ◽  
Image Edges

In the fields of image processing, feature detection, the edge detection is an important aspect. For detection of sharp changes in the properties of an image, edges are recognized as important factors which provides more information or data regarding the analysis of an image. In this work coding of various edge detection algorithms such as Sobel, Canny, etc. have been done on the MATLAB software, also this work is implemented on the FPGA Nexys 4 DDR board. The results are then displayed on a VGA screen. The implementation of this work using Verilog language of FPGA has been executed on Vivado 18.2 software tool.

scholarly journals Vietnamese character recognition based on CNN model with reduced character classes

2021 ◽  
Vol 10 (2) ◽  
pp. 962-969
Author(s):  
Thi Ha Phan ◽  
Duc Chung Tran ◽  
Mohd Fadzil Hassan
Keyword(s):  
Mobile Application ◽  
Character Recognition ◽  
Detection Algorithm ◽  
Classification Model ◽  
Canny Edge Detection ◽  
Edge Detection Algorithm ◽  
Canny Edge ◽  
Similar Character ◽  
Text Content ◽  
Canny Edge Detection Algorithm

This article will detail the steps to build and train the convolutional neural network (CNN) model for Vietnamese character recognition in educational books. Based on this model, a mobile application for extracting text content from images in Vietnamese textbooks was built using OpenCV and Canny edge detection algorithm. There are 178 characters classes in Vietnamese with accents. However, within the scope of Vietnamese character recognition in textbooks, some classes of characters only differ in terms of actual sizes, such as “c” and “C”, “o” and “O”. Therefore, the authors built the classification model for 138 Vietnamese character classes after filtering out similar character classes to increase the model's effectiveness.

scholarly journals Enhancement of digital chest images using a modified Sobel edge detection algorithm

2021 ◽  
Vol 24 (3) ◽  
pp. 1718
Author(s):  
Archana J. N. ◽  
Aishwarya P. ◽  
Hanson Joseph
Keyword(s):  
Edge Detection ◽  
Detection Algorithm ◽  
Interstitial Lung Diseases ◽  
Internal Organs ◽  
Edge Detection Algorithm ◽  
Sobel Operator ◽  
Digital Chest ◽  
Sobel Edge Detection ◽  
The Laplace Operator ◽  
Lung Ct

Computed tomography (CT) images are an essential factor in the diagnosing procedure for various diseases affecting the internal organs. Edge detection can be used for the appropriate enhancement of the lung CT scan images for the diagnosis of the various interstitial lung diseases (ILD). In order to solve the issues of edge detection provided by the traditional Sobel operator, the paper proposes a Sobel 12D edge detection algorithm which uses the additional direction templates for the better identification of the edge details. First, the vertical and horizontal directions available in the traditional Sobel operator are extended to few more directions (a total of 12 directions) which enhances the edge extraction ability. Next part, compute the edge detected image using the Sobel 12D, Laplace, Prewitt, Robert’s Cross and Scharr operators for edge detection separately. It is followed by image fusion method which optimizes the edge detection by combining the edge detected images obtained using the Sobel 12D approach and the Laplace operator. The experimental results shows that the proposed algorithms generates a better detection of the edges than the other edge detection operators.

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