Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Jurnal Teknik ITS Jurnal Riset Industri Hasil Hutan CCIT (Creative Communication and Innovative Technology) Journal Fairness and Justice: Jurnal Ilmiah Ilmu Hukum SEMAR (Jurnal Ilmu Pengetahuan, Teknologi, dan Seni bagi Masyarakat) Causa: Jurnal Hukum dan Kewarganegaraan
Djoko Purwanto
Kementerian Perindustrian
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Education Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Social Sciences

Published : 12 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : CCIT (Creative Communication and Innovative Technology) Journal

 1 
EDGE DETECTION USING CELLULAR NEURAL NETWORK AND TEMPLATE OPTIMIZATION Widodo Budiharto; Djoko Purwanto; Mauridhi Hery Purnomo
CCIT Journal Vol 4 No 1 (2010): CCIT JOURNAL
Publisher : Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (562.878 KB) | DOI: 10.33050/ccit.v4i1.358

Abstract

Result of edge detection using CNN could be not optimal, because the optimal result is based on template applied to the images. During the first years after the introduction of the CNN, many templates were designed by cut and try techniques. Today, several methods are available for generating CNN templates or algorithms. In this paper, we presented a method to make the optimal result of edge detection by using TEMPO (Template Optimization). Result shown that template optimization improves the image quality of the edges and noise are reduced. Simulation for edge detection uses CANDY Simulator, then we implementing the program and optimized template using MATLAB. Comparing to Canny and Sobel operators, image shapes result from CNN edge detector also show more realistic and effective to user.
Co-Authors Ahmad Firdaus Catur Sugiarto Dadet Pramadihanto Hendra Kusuma Kamal Arief Mauridhi Hery Purnomo Muhammad Yusuf Indra Purnama Pram Suryanadi Rinne Nintasari Sunarjanto Sunarjanto Tastaftiyan Risfandy Widodo Budiharto Zainal Arief