Automatic reading recognition system of pointer meters using WSNs with on-sensor image processing

The use of the NPR (Number Plate Recognition) is a structure expected to assist confirm the number tags of cars. This structure is anticipated to have the real goal of the security system. This structure is based on an image planning system. This scheme helps to distinguish between the number plates of the cars, to prepare them and to use the information taken care of for further methodology such as securing, empowering the car to pass or to expel the car. NPR is an image scheduling development that utilizes the number (license) plate to acknowledge the car. The goal is to structure a gainful altered attested vehicle unmistakable proof scheme by the use of car number plateThe system is carried out along the route of security control of a particularly restricted area, such as military areas or area around the finest public working settings, such as the Parliament, the Supreme Court, etc. First, the produced system receives a image of the car. The region of the vehicle number plate is evacuated using the picture division in the picture. The optical character affirmation method is used to confirm the character. The resulting information is then used to distinguish and record the information in the database. The structure is performed and impersonated in Python, and the execution is tried on a licensed image. It is seen from the outset that the produced structure acknowledges and sees the car amount vividly.

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2A2-E12 An Environment Recognition System for a Wheel Type Mobile Robot with Rough Terrain Movement : Third Report: Instrument of Self-Localization System using Image Processing

The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) ◽

10.1299/jsmermd.2009._2a2-e12_1 ◽

2009 ◽

Vol 2009 (0) ◽

pp. _2A2-E12_1-_2A2-E12_2

Author(s):

Atushi KANDA ◽

Kazuo ISHII ◽

Masanori SATO

Keyword(s):

Image Processing ◽

Mobile Robot ◽

Recognition System ◽

Rough Terrain ◽

Localization System ◽

Environment Recognition

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Image Processing: Capturing Student Attendance Data

INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY ◽

10.24297/ijct.v16i7.6390 ◽

2017 ◽

Vol 16 (7) ◽

pp. 7002-7009

Author(s):

Hendra - Kurniawan ◽

Melda Agarina ◽

Suhendro Yusuf Irianto

Keyword(s):

Image Processing ◽

Learning Process ◽

Teaching And Learning ◽

Process Model ◽

Tertiary Education ◽

Recognition System ◽

Student Attendance ◽

Processing Application ◽

Student Activities ◽

Facial Recognition System

Role of the student attendance record is very important in the primary, secondary, and tertiary education. The purpose of this record is monitoring student activity in the teaching and learning process and regarded as one of the important learning assessments. Moreover, a data processing for recording the student attendance is currently done in various ways such as fingerprint, radio frequent identification (RFID), facial recognition system, android-based application, and others. However, many conventional ways (i.e., using paper-based system) are still used, especially in Indonesia. This is because several universities still rarely have enough funds for developing innovative systems. In this research, the image processing application for capturing student attendance data was built. The objective of this research was to provide an efficient alternative to monitor student activities in teaching and learning process. The image processing produced the information related to student attendance by scanning the attendance file through jpg/jpeg using learning vector quantization (LVG) as the process model.

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Plant Diseases Recognition Based on Image Processing Technology

Journal of Electrical and Computer Engineering ◽

10.1155/2018/6070129 ◽

2018 ◽

Vol 2018 ◽

pp. 1-7 ◽

Cited By ~ 10

Author(s):

Guiling Sun ◽

Xinglong Jia ◽

Tianyu Geng

Keyword(s):

Image Processing ◽

Image Segmentation ◽

Linear Regression ◽

Multiple Linear Regression ◽

Image Recognition ◽

Color Image ◽

Regional Growth ◽

Recognition System ◽

Plant Diseases ◽

Image Feature

A new image recognition system based on multiple linear regression is proposed. Particularly, there are a number of innovations in image segmentation and recognition system. In image segmentation, an improved histogram segmentation method which can calculate threshold automatically and accurately is proposed. Meanwhile, the regional growth method and true color image processing are combined with this system to improve the accuracy and intelligence. While creating the recognition system, multiple linear regression and image feature extraction are utilized. After evaluating the results of different image training libraries, the system is proved to have effective image recognition ability, high precision, and reliability.

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