Library Automation and Digital Archive
LONTAR
Fakultas Ilmu Komputer
Universitas Indonesia

Pencarian Sederhana

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Call Number SEM-372
Collection Type Indeks Artikel prosiding/Sem
Title Shoreline Change Detection Based on Multispectral Images Using 2D-Principial Component Analysis of Band Images And Histogram of Oriented Gradient Features
Author I Gede Wahyu Surya Dharma, Aniati Murni Arymurthy;
Publisher ICACSIS 2017 International Conference on Advanced Computer Science Information System. Hal 315-320
Subject Feature Extraction, classification, shoreline, multispectral image, 2DPCA-SVM-HOG
Location
Lokasi : Perpustakaan Fakultas Ilmu Komputer
Nomor Panggil ID Koleksi Status
SEM-372 TERSEDIA
Tidak ada review pada koleksi ini: 47301
Abstract- Shoreline is a boundary area between land and sea, where there are few phenomena that unique and dynamic. This phenomenon includes abrasion erosion and sedimentation. Development of infrastructure and reclamation is human action that can alter the ecosystem as well as the order of shoreline. Observation shoreline is a field that is very useful for Indonesia because Indonesia is an archipelagic country consisting of many islands. Danger from the sea could come at any time and could be very dangerous for human life, so it is important to observe, to monitor and to maintain the shoreline. This study used Support Vector Machine (SVM) as classification method, and principal component analysis of the band images and histogram of oriented gradient as feature extraction for shape feature. Multi temporal Landsat 8 acquired in 2016. The result of this study shown that 85% of shoreline in 2016 changed after applied image enhancement compared to shoreline in year of 1996.