Year: 2019
Type: article
Abstract: Estimating the age into different categories i.e. 1. Childhood (0-12 years) 2. Young Age (13-25years) 3. Middle age (26-40years) 4. Senior age (40-60years) 5.Senior Citizens(more than 60 years) using fuzzy model is a challenging task for researchers .There are many classifiers to classify the data into different age groups.In our proposed method age is classified into different age groups based on the transition count of Local Binary Patterns for Left angular pattern and Right angular pattern.Age Estimation is essential in many applications like where there is no entry for the people whose age is less than particular age, biometrics, crime detection and so on
Authors: MOKA UMA DEVI, UPPU RAVI BABU
Institution: Acharya Nagarjuna University
Language: English
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W3000465788