Knowledge Engineering and Data Science
Vol 3, No 2 (2020)

Tanned and Synthetic Leather Classification Based on Images Texture with Convolutional Neural Network

Faadihilah Ahnaf Faiz (Ahmad Dahlan University)
Ahmad Azhari (Ahmad Dahlan University)



Article Info

Publish Date
31 Dec 2020

Abstract

Tanned leather is an output from complex processes called tanning. Leather tanning is an important step that used to protect the fiber or protein structure of animal’s skin. Another reason of tanning process is to prevent the animal’s skin from any defect or rot. After the tanning is complete, the leather can be applied to produce a wide variety of leather products. Thus, the leather prices usually more expensive because it takes longer time in process. Another way to get cheaper price is make non-animal leather that usually known as synthetic or imitation leather. The purpose of this paper is to classify the tanned leather and synthetic leather by using Convolutional Neural Network. The tanned leather consist of cow, goat and sheep leathers. The proposed method will classify into four class, they are cow, goat, sheep and synthetic leathers. In each class consist of 160 images with 448x448 pixels size as the input data. With CNN method, this research shows a good result for the accuracy about 92.1%.

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Journal Info

Abbrev

keds

Publisher

Subject

Computer Science & IT Engineering

Description

Knowledge Engineering and Data Science (2597-4637), KEDS, brings together researchers, industry practitioners, and potential users, to promote collaborations, exchange ideas and practices, discuss new opportunities, and investigate analytics frameworks on data-driven and knowledge base ...