Penerapan Learning Vector Quantization (LVQ) Algorthm untuk Pengenalan Karakter Melalui Pola Wajah
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Khalifa, Sri Aulia
Manjawakang, Abdul Haris
Sikumbang, Hengki
Manjawakang, Abdul Haris
Sikumbang, Hengki
Subject
Teknik Informatika
Datestamp
2022-09-26 06:31:57
Abstract :
One branch of psychological science that studies the relationship between characters and the shape of the face is the physiognomy where in this science every part of the face from the forehead to the chin have a type of shape and character that represents each shape, knowing this science one can easily establish a good social relationship by getting to know more in character from interlocu or co-workers and others. However, not everyone can read a person's character through the face because each human being has the shape of a face that is diverse and diverse characters, therefore only people who study and delve into the science of physiognomy can read the characters someone from the face. To solve the problem, it is necessary to apply this physiognomy science in an intelligent computing system with using the Learning Vector Quantization method which is one of the supervised learning methods that can be applied to classification issues. Which in the modeling system created, the system will recognize characters automatically by using facial imagery as data for the process training and classification of lvq methods that have previously gone through the pre-processing phase with the aim of so that facial imagery can be processed at the Next. At this pre-processing stage is used canny edge detection to obtain the shape pattern and binary values of the part of the face you want to recognize namely the eyes, nose and lips
One branch of psychological science that studies the relationship between characters and the shape of the face is the physiognomy where in this science every part of the face from the forehead to the chin have a type of shape and character that represents each shape, knowing this science one can easily establish a good social relationship by getting to know more in character from interlocu or co-workers and others. However, not everyone can read a person's character through the face because each human being has the shape of a face that is diverse and diverse characters, therefore only people who study and delve into the science of physiognomy can read the characters someone from the face. To solve the problem, it is necessary to apply this physiognomy science in an intelligent computing system with using the Learning Vector Quantization method which is one of the supervised learning methods that can be applied to classification issues. Which in the modeling system created, the system will recognize characters automatically by using facial imagery as data for the process training and classification of lvq methods that have previously gone through the pre-processing phase with the aim of so that facial imagery can be processed at the Next. At this pre-processing stage is used canny edge detection to obtain the shape pattern and binary values of the part of the face you want to recognize namely the eyes, nose and lips
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