Smartphone Technology Applications for Milkfish Image Segmentation Using OpenCV Library
Dublin Core
Title
Smartphone Technology Applications for Milkfish Image Segmentation Using OpenCV Library
Subject
Library OpenCV
Citra Segmentation
Android Application
Technology Smartphone
Description
This research presents the use of smartphone technology to assist fisheries work. Specifically, we designed an Android application that utilizes a camera connected to the internet to detect RGB image objects and then convert them to HSV and gray scale. In this paper, Android-based smartphone technology using image processing methods will be discussed, a digital tool that provides fish detection results in the form of length, width, and weight used to determine the price of fish. This application was created using features provided by the OpenCV library to produce binary images. Three main challenges highlighted during application design including C ++ QT were used to build the user interface, the contour-active method was used to divide and separate image objects from the back-ground, while the clever edge edge method was used to improve the outline ap-pearance of objects. Both methods are implemented on the Android platform and utilize smartphone cameras as an identification tool. This application makes it possible to provide many benefits and great benefits for farm farmers but on the other hand will create technological gaps
Creator
Qashlim, Akhmad
Basri, Basri
Haeruddin, Haeruddin
Ardan, Ardan
Nurtanio, Inggrid
Ilham, Amil Ahmad
Source
International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 08 (2020); pp. 150-163
1865-7923
Publisher
International Association of Online Engineering (IAOE), Vienna, Austria
Date
2020-05-20
Rights
Copyright (c) 2020 Akhmad Qashlim
Relation
Format
application/pdf
Language
eng
Type
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Identifier
Citation
Akhmad Qashlim et al., Smartphone Technology Applications for Milkfish Image Segmentation Using OpenCV Library, International Association of Online Engineering (IAOE), Vienna, Austria, 2020, accessed November 16, 2024, https://igi.indrastra.com/items/show/1616