Pre-trained convolutional networks for classification of training leather image

Sri, Winiarti and Prahara, Adhi and Murinto, Murinto and Dewi Pramudia, ismi (2018) Pre-trained convolutional networks for classification of training leather image. [Artikel Dosen]

Text HASIL CEK_Murinto_Pre-Trained Convolutional Neural Network for Classification of Tanning Leather Image.pdf Download (2MB)

Abstract

Leather craft products, such as belt, gloves, shoes,
bag, and wallet are mainly originated from cow, crocodile, lizard,
goat, sheep, buffalo, and stingray skin. Before the skins are used
as leather craft materials, they go through a tanning process.
With the rapid development of leather craft industry, an
automation system for leather tanning factories is important to
achieve large scale production in order to meet the demand of
leather craft materials. The challenges in automatic leather
grading system based on type and quality of leather are the skin
color and texture after tanning process will have a large variety
within the same skin category and have high similarity with the
other skin categories. Furthermore, skin from different part of
animal body may have different color and texture. Therefore, a
leather classification method on tanning leather image is proposed. The method uses pre-trained deep convolution neural network (CNN) to extract rich features from tanning leather image and Support Vector Machine (SVM) to classify the features into several types of leather. Performance evaluation shows that the proposed method can classify various types of
leather with good accuracy and superior to other state-of-the-art leather classification method in terms of accuracy and computational time.

Item Type:	Artikel Dosen
Keyword:	Leather classification; tanning leather; convolution neural network (CNN); deep learning; support vector machine (SVM)
Subjects:	Q Science > Q Science (General)
Divisi / Prodi:	Faculty of Industrial Technology (Fakultas Teknologi Industri) > S1-Informatics Engineering (S1-Teknik Informatika)
Depositing User:	murinto murinto
Date Deposited:	18 Apr 2023 09:49
Last Modified:	23 Sep 2023 06:06
URI:	http://eprints.uad.ac.id/id/eprint/43019

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