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Journal of ICT Research and Applications
Published by Institut Teknologi Bandung
ISSN : 23375787     EISSN : 23385499     DOI : https://doi.org/10.5614/itbj.ict.res.appl.
Core Subject : Science,
Computer Science & IT
Journal of ICT Research and Applications welcomes full research articles in the area of Information and Communication Technology from the following subject areas: Information Theory, Signal Processing, Electronics, Computer Network, Telecommunication, Wireless & Mobile Computing, Internet Technology, Multimedia, Software Engineering, Computer Science, Information System and Knowledge Management.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 4 Documents
 1 
Search results for , issue "Vol. 5 No. 1 (2011)" : 4 Documents clear
Characters Segmentation of Cursive Handwritten Words based on Contour Analysis and Neural Network Validation Fajri Kurniawan; Mohd. Shafry Mohd. Rahim; Ni'matus Sholihah; Akmal Rakhmadi; Dzulkifli Mohamad
Journal of ICT Research and Applications Vol. 5 No. 1 (2011)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.2011.5.1.1

Abstract

This paper presents a robust algorithm to identify the letter boundaries in images of unconstrained handwritten word . The proposed algorithm is based on  vertical  contour  analysis.  Proposed  algorithm  is  performed  to  generate  presegmentation by analyzing the vertical contours from right to left. The unwanted segmentation  points  are  reduced  using  neural  network  validation  to  improve accuracy  of  segmentation.  The  neural  network  is  utilized  to  validate segmentation  points.  The  experiments  are  performed  on  the  IAM  benchmark database.  The  results  are  showing  that  the  proposed  algorithm  capable  to accurately locating the letter boundaries for unconstrained handwritten words.
Free Model of Sentence Classifier for Automatic Extraction of Topic Sentences M.L. Khodra; D.H. Widyantoro; E.A. Aziz; B.R. Trilaksono
Journal of ICT Research and Applications Vol. 5 No. 1 (2011)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.2011.5.1.2

Abstract

This  research  employs  free  model  that  uses  only  sentential  features without paragraph context  to extract topic sentences of a paragraph. For finding optimal  combination  of  features,  corpus-based  classification  is  used  for constructing a sentence classifier  as the model.  The sentence classifier is trained by  using Support Vector Machine  (SVM).  The experiment shows that position and meta-discourse features are more important  than syntactic features  to extract topic  sentence,  and  the  best  performer  (80.68%)  is  SVM  classifier  with  all features. 
The Effectiveness of Chosen Partial Anthropometric Measurements in Individualizing Head-Related Transfer Functions on Median Plane Hugeng Hugeng; Wahidin Wahab; Dadang Gunawan
Journal of ICT Research and Applications Vol. 5 No. 1 (2011)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.2011.5.1.3

Abstract

Individualized  head-related  impulse  responses  (HRIRs)  to  perfectly suit  a  particular  listener  remains  an  open  problem  in  the  area  of  HRIRs modeling.   We  have  modeled  the  whole  range  of  magnitude  of  head-related transfer  functions  (HRTFs)  in  frequency  domain  via  principal  components analysis  (PCA),  where  37  persons  were  subjected  to  sound  sources  on  median plane.   We  found  that  a  linear  combination  of  only  10  orthonormal  basis functions was sufficient to satisfactorily model individual magnitude HRTFs. It was our goal to form multiple linear regressions (MLR) between weights of basis functions acquired from PCA and chosen partial anthropometric  measurements in  order  to  individualize  a  particular  listener's  H RTFs  with  his  or  her  own anthropometries. We proposed a novel individualization method based on MLR of  weights  of  basis  functions  by  employing  only  8  out  of  27  anthropometric measurements.  The  experiments'  results  showed  the  proposed  method,  with mean  error  of  11.21%,  outperformed  our  previous  works  on  individualizing minimum  phase  HRIRs  (mean  error  22.50%)  and  magnitude  HRTFs  on horizontal  plane  (mean  error  12.17%)  as  well  as  similar  researches.  The proposed  individualization  method  showed  that  the  individualized  magnitude HRTFs could be well estimated as the original ones with a slight error.  Thus  the eight  chosen  anthropometric  measurements  showed  their  effectiveness  in individualizing magnitude HRTFs particularly on median plane. 
Digital Dermatoscopy Method for Human Skin Roughness Analysis Suprijanto Suprijanto; V. Nadhira; Dyah A. Lestari; E. Juliastuti; Sasanti T. Darijanto
Journal of ICT Research and Applications Vol. 5 No. 1 (2011)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.2011.5.1.4

Abstract

In this study we  propose a digital dermatoscopy  method to measure the human skin roughness. By using this method we eliminate the use of silicon replica.  Digital  dermatoscopy  consists  of  handheld  digital  microscope,  image processing  and  information  extraction  of  skin  roughness  level.  To  reduce  the noise due to the variation of reflection factor on the skin we use  median filter. Hence, by Fourier transform the skin texture is imaged in terms of 2D frequencyspatial  distribution.  Skin  roughness  is  determined  from  its  entropy,  where  the roughness level is proportional to the entropy.  Three types of experiment have been performed by evaluating: (i) the skin replicas; (ii)  young and elderly skin; and (iii) seven volunteers treated by anti wrinkle cosmetic in three weeks period. We find that for the first and second experiment that our system did manage to quantify the roughness, while on the third experiment, six of seven volunteers, the roughness are succeeded to identify.

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