Detecting object using combination of sharpening and edge detection method

Irsyadi Yani, M. A. Hannan, Hassan Basri, Edgar Scavino, Noor Ezlin bin Ahmad Basri

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Object detection is one of the most important preprocessing steps in object recognition and identification systems. This can be done by searching and indexing still image or video containing object in various size, position and background. This paper deals the beverage cans detection system on the moving conveyor belt using combination of sharpening and edge detection method. Experimental results show that the accuracy of the cans detection system is strongly enough which is based on the quality and quantity of the data used in the database. It also shows that the sharpening and edge detection algorithm improves the detecting speed significantly. © EuroJournals Publishing, Inc. 2009.
Original languageEnglish
Pages (from-to)122-128
Number of pages109
JournalEuropean Journal of Scientific Research
Publication statusPublished - 01 Jan 2009
Externally publishedYes

Fingerprint

Beverages
Edge Detection
Edge detection
detection method
Databases
Image Indexing
Video Indexing
Object Detection
Object recognition
Object Recognition
System Identification
Preprocessing
Identification (control systems)
cans
Experimental Results
methodology
beverages
Object
Data Accuracy
detection

Cite this

Yani, Irsyadi ; Hannan, M. A. ; Basri, Hassan ; Scavino, Edgar ; Basri, Noor Ezlin bin Ahmad. / Detecting object using combination of sharpening and edge detection method. In: European Journal of Scientific Research. 2009 ; pp. 122-128.
@article{ebdf85985fbc48179e83aea28e28da92,
title = "Detecting object using combination of sharpening and edge detection method",
abstract = "Object detection is one of the most important preprocessing steps in object recognition and identification systems. This can be done by searching and indexing still image or video containing object in various size, position and background. This paper deals the beverage cans detection system on the moving conveyor belt using combination of sharpening and edge detection method. Experimental results show that the accuracy of the cans detection system is strongly enough which is based on the quality and quantity of the data used in the database. It also shows that the sharpening and edge detection algorithm improves the detecting speed significantly. {\circledC} EuroJournals Publishing, Inc. 2009.",
author = "Irsyadi Yani and Hannan, {M. A.} and Hassan Basri and Edgar Scavino and Basri, {Noor Ezlin bin Ahmad}",
year = "2009",
month = "1",
day = "1",
language = "English",
pages = "122--128",
journal = "European Journal of Scientific Research",
issn = "1450-202X",
publisher = "European Journals Inc.",

}

Detecting object using combination of sharpening and edge detection method. / Yani, Irsyadi; Hannan, M. A.; Basri, Hassan; Scavino, Edgar; Basri, Noor Ezlin bin Ahmad.

In: European Journal of Scientific Research, 01.01.2009, p. 122-128.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Detecting object using combination of sharpening and edge detection method

AU - Yani, Irsyadi

AU - Hannan, M. A.

AU - Basri, Hassan

AU - Scavino, Edgar

AU - Basri, Noor Ezlin bin Ahmad

PY - 2009/1/1

Y1 - 2009/1/1

N2 - Object detection is one of the most important preprocessing steps in object recognition and identification systems. This can be done by searching and indexing still image or video containing object in various size, position and background. This paper deals the beverage cans detection system on the moving conveyor belt using combination of sharpening and edge detection method. Experimental results show that the accuracy of the cans detection system is strongly enough which is based on the quality and quantity of the data used in the database. It also shows that the sharpening and edge detection algorithm improves the detecting speed significantly. © EuroJournals Publishing, Inc. 2009.

AB - Object detection is one of the most important preprocessing steps in object recognition and identification systems. This can be done by searching and indexing still image or video containing object in various size, position and background. This paper deals the beverage cans detection system on the moving conveyor belt using combination of sharpening and edge detection method. Experimental results show that the accuracy of the cans detection system is strongly enough which is based on the quality and quantity of the data used in the database. It also shows that the sharpening and edge detection algorithm improves the detecting speed significantly. © EuroJournals Publishing, Inc. 2009.

UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=67649210335&origin=inward

UR - https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=67649210335&origin=inward

M3 - Article

SP - 122

EP - 128

JO - European Journal of Scientific Research

JF - European Journal of Scientific Research

SN - 1450-202X

ER -