scholarly journals Indian Currency Denomination Recognition and Fake Currency Identification

2021 ◽  
Vol 2089 (1) ◽  
pp. 012008
Author(s):  
B Padmaja ◽  
P Naga Shyam Bhargav ◽  
H Ganga Sagar ◽  
B Diwakar Nayak ◽  
M Bhushan Rao
Keyword(s):  
Template Matching ◽  
Visually Impaired ◽  
Senior Citizens ◽  
Region Of Interest ◽  
Automated System ◽  
Canny Edge Detection ◽  
Matching Algorithm ◽  
Multi Scale ◽  
Currency Note ◽  
Canny Edge

Abstract Visually impaired and senior citizens find it difficult to identify different banknotes, driving the need for an automated system to recognize currency notes. This study proposes recognizing Indian currency notes of various denominations using Deep Learning through the CNN model. While not recognizing currency notes is one issue, identifying fake notes is another major issue. Currency counterfeiting is the illegal imitation of currency to deceive its recipient. The current existing methodologies for identifying a phony note rely on hardware. A method completely devoid of hardware that relies on specific security features to help distinguish a legitimate currency note from an illegitimate one is much needed. These features are extracted using the boundary box region of interest (ROI) and Canny Edge detection in OpenCV implemented in Python, and the multi scale template matching algorithm is applied to match the security features and differentiate fake notes from legitimate notes.

The Assembly Error Detection of Automotive Airbag Based on Machine Vision

2015 ◽  
Vol 738-739 ◽  
pp. 694-698
Author(s):  
Xiao Dong Wang ◽  
Qi Liu ◽  
Wei Zhang
Keyword(s):  
Machine Vision ◽  
Error Detection ◽  
Template Matching ◽  
Assembly Line ◽  
Detection Method ◽  
Ccd Camera ◽  
Processing Method ◽  
Canny Edge Detection ◽  
Canny Edge ◽  
Assembly Error

Based on the principle of machine vision technology, we designed a methodto detect the outline dimensions of automotive airbag quickly and accurately. We Used CCD camera obtain the airbag image, through the image processing method ofsmooth filtering andgray-scale transformationto complete pre-processing, finally applied Canny edge detection operator to extract the boundary of the airbag contour features,and then took the template matching methodto detect assemble error of the airbag image whether meet the requirement.The results show that the detection method have a higher precision, and the time is very short, it can improve the sampled positioningerror detection for the all checks image recognition detection, suitable for application in real-time online detection of airbag assembly line.

scholarly journals Optical Disc and Blood Vessel Segmentation in Retinal Fundus Images

2019 ◽  
Vol 8 (3) ◽  
pp. 67
Author(s):  
Amira B. Sallow ◽  
Hawkar Kh. Shaikha
Keyword(s):  
Blood Vessel ◽  
Template Matching ◽  
Cross Correlation ◽  
Region Of Interest ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Original Image ◽  
Matching Algorithm ◽  
A New Technique ◽  
Retinal Fundus

Segmentation of optical disk (OD) and blood vessel is one of the significant steps in automatic diabetic retinopathy (DR) detecting. In this paper, a new technique is presented for OD segmentation that depends on the histogram template matching algorithm and OD size. In addition, Kirsch method is used for Blood Vessel (BV) segmentation which is one of the popular methods in the edge detection and image processing technique. The template matching algorithm is used for finding the center of the OD. In this step, the histogram of each RGB (Red, Green, and Blue) planes are founded and then the cross-correlation is founded between the template and the original image, OD location is the point with maximum cross-correlation between them. The OD size varies according to the camera field of sight and the resolution of the original image. The rectangle size of OD is not the same for various databases, the estimated size for DRIVE, STARE, DIARTDB0, and DIARTDB1 are 80×80, 140×140, 190×190, and 190×190 respectively. After finding the OD center and rectangle size of OD, a binary mask is created with Region of Interest (ROI) for segmenting the OD. The DIARTDB0 is used to evaluate the proposed technique, the result is robust and vital with an accuracy of 96%.

scholarly journals ROI based Indonesian Paper Currency Recognition Using Canny Edge Detection

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Ahmad Imam Rauyani ◽  
Muhammad Hamka Ibrahim ◽  
Subuh Pramono
Keyword(s):  
Template Matching ◽  
Region Of Interest ◽  
Image Features ◽  
Spatial Transformation ◽  
Reference Region ◽  
Paper Currency ◽  
Canny Edge ◽  
Edge Method ◽  
Edge Features ◽  
Python Programming

Paper currency recognition is important for automatic payment system. The paper performs a nominal paper detection process using image processing with canny method implemented in python programming language. The canny method is used to find edge features in the nominal currency. By using template matching of image reference, region of interest (ROI) of nominal value is extracted so that it can be used in any orientation of  paper currency image. The ROI of nominal image is processed by canny edge method and spatial transformation to strengthen the image features and being processed by template matching to decide nominal currency. The study has successfully tested nominal value of 1000, 2000, 5000, 10000, 20000, 50000, and 100000 Indonesia banknotes which then the currency value will appear in the value variable in python.

scholarly journals SISTEM IDENTIFIKASI PLAT NOMOR KENDARAAN DALAM PENERAPAN REGULASI PAJAK BERBASIS CITRA DIGITAL

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Oktaf Brillian Kharisma
Keyword(s):  
Edge Detection ◽  
Template Matching ◽  
Canny Edge Detection ◽  
Canny Edge

Sistem identifikasi pajak kendaraan berdasarkan plat nomor untuk memudahkan pendataan dalam penerapan regulasi pemutasian kendaraan disuatu wilayah sangatlah penting. Kasus di provinsi Riau, kendaraan yang beroperasi melebihi 3 bulan di luar wilayah diwajibkan segera memutasi pajak kendaraannya. Identifikasi masih dilakukan secara manual dengan melibatkan orang untuk melakukan pendataan. Sehingga, kurang efektif dan efisien. Tujuan penelitian untuk menghasilkan sistem yang memudahkan dalam mengidentifikasi dan mengumpulkan data plat nomor kendaraan untuk pajak daerah menggunakan algoritma canny edge detection dan template matching. Sistem dibuat menggunakan aplikasi GUI Matlab dan hasil langsung dikirim ke aplikasi website. Data video yang di proses beresolusi 1280x720 pixel dengan menghasilkan akurasi identifikasi plat nomor kendaraan mencapai 87,5%.

A Fast Binocular Vision Stereo Matching Algorithm

2014 ◽  
Vol 556-562 ◽  
pp. 3735-3738
Author(s):  
Hui Zhang ◽  
Ling Tao Zhang ◽  
Yi Ren
Keyword(s):  
Stereo Matching ◽  
Computational Cost ◽  
Stereo Image ◽  
Feature Points ◽  
Image Pair ◽  
Canny Operator ◽  
Canny Edge Detection ◽  
Matching Algorithm ◽  
Canny Edge ◽  
Image Edge

In this paper we present a fast indoor stereo matching algorithm based on canny edge detection and line moments. We first detect image edge by using Canny operator, then find the target objects according line moments, the feature points of the objects’ contours are extracted. Finally, matching the pixel in stereo image pair according the angle vector. The algorithm effectively reduces the computational complexity, computational cost is decreased greatly. The experimental results show that the algorithm is possible and valid.

scholarly journals Fruit monitoring system using multi-layered neural network

2018 ◽  
Vol 7 (3) ◽  
pp. 1439
Author(s):  
Rui Xu ◽  
Tae Hyun Cho ◽  
Chang Kil Kim ◽  
Bonghwan Kim ◽  
In Soo Lee
Keyword(s):  
Neural Network ◽  
Monitoring System ◽  
Graphical User Interface ◽  
Recognition Rate ◽  
Region Of Interest ◽  
Maturity Level ◽  
Canny Edge Detection ◽  
The Neural Network ◽  
Canny Edge ◽  
Very High

A fruit monitoring system based on image processing technology and multi-layer neural network is proposed. The advantage of the proposed fruit monitoring system allows it to be remotely controlled by PCs and the graphical user interface (GUI) program by LabVIEW which has been designed for more intuitive and convenient operation of this system. In addition, the neural network can reduce nonlinearity of the system compared to the calculation based system. Therefore, experienced workers and novices can easily judge the ripeness of the fruits using the GUI program without necessarily going to the orchards. In this study, the color is used as a criterion to judge the maturity of tomatoes. Ripe tomatoes will appear to be red, while the unripe tomatoes will be green in color. The region of interest (ROI) function and Canny edge detection are applied to crop the image and remove the background, then the pixel data obtained are to supply the use of neural network. After that the maturity level of tomatoes is judged by the neural network. In laboratory test, 50 experiments have been down, 48 of which were successful, 2 of which failed, so the recognition rate was 96%. The experiments of this fruit monitoring system in the greenhouse on real growing tomatoes has been conducted. Therefore, 10 experiments on the red and green tomatoes has been conducted, respectively. As a result, the recognition rate of the red tomatoes is 100%, and recognition rate of the green tomatoes is 90%. The experimental results show that the proposed mobile fruit monitoring system has a very high recognition rate of accuracy.  

PENDETEKSIAN TINGKAT KEPADATAN JALAN MENGGUNAKAN METODE CANNY EDGE DETECTION

2020 ◽  
Vol 25 (3) ◽  
pp. 239-248
Author(s):  
Arimbi Kurniasari ◽  
Jalinas
Keyword(s):  
Edge Detection ◽  
Region Of Interest ◽  
Canny Edge Detection ◽  
Canny Edge

Ruang lalu lintas merupakan sarana yang digunakan sebagai gerak pindah orang, kendaraan, dan barang yang berupa jalan dan fasilitas pendukung. Informasi kepadatan jalan merupakan informasi yang sangat penting untuk mendeteksi kepadatan dan menghitung lalu lintas. Pengolahan citra diperlukan untuk mendapatkan informasi mengenai kepadatan jalan baik menggunakan citra maupun video kondisi jalan. Penelitian ini mengimplementasikan metode deteksi tepi Canny dengan menentukan koordinat Region of Interest (ROI) dan menghitung persentase kepadatan pada data video sesuai area ROI yang sudah ditentukan. Hasil penelitian diharapkan dapat mendeteksi kendaraan di jalan dan menentukan tingkat kepadatan jalan dari hasil deteksi menggunakan metode Canny. Setelah dilakukan uji coba sistem didapat hasil yaitu penentuan ROI di jalan menggunakan 4 buah titik koordinat, metode Canny berhasil mendeteksi kendaraan yang berada di jalan, dan dapat menentukan persentase kepadatan untuk menghasilkan status kepadatan lalu lintas.

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