- Universiti Teknologi Malaysia

PENGECAMAN IMEJ KAPAL TERBANG MENGGUNAKAN
TEKNIK LMI" TMI DAN KMI BAGI KAEDAH SOM
NURULLIZ AH BINTI MAHIDIN
Laporan Projek ini dikemukakan
Sebagaimemenuhisebahagiandaripadasyarat
penganugerahan
ljazah SarjanaMuda Sains(SainsKomputer)
F'akultiSainsKomputer dan SistemMaklumat
Universiti TeknologiMalaysia
MEr,2008
I
ABSTRAK
Mata merupakansuatuanugerahyangtidak ternilai di manamelaluinyakita
dapatmelihat apayangberlakudi sekelilingkita. Mata bertindaksebagaikamera
iaitu denganmenangkapsuatuimej untuk dihantardandiprosesoleh otak. Maka
giat menciptasatumesinbaruyangberkait
tidak hairanlahsekiranya,parapenyelidik
rapatdengansistempenglihatanmanusia.Bagi mesinbaruini terdapatdua(2) fasa
yangpentingiaitu fasapengekstrakan
imej danfasapengelasan.Bagi melakukan
fasapengekstrakan
imej teknik momentak varianiaitu LegendreMomentsInvariant
(LMD, Tchebichef
MomentsInvariant(TMI), danKrawtchoukMomentInvariant
(KMD digunakanmanakalakaedahrangkaianneuraliaitu Self-OrganisingMap
(SOM)digunakanuntuk membuatpengelasan
imej danpengecaman
terhadapobjek
domainyangdipilih iaitu kapalterbang.Hasil yangdiperolehidaripadakajian
menunjukkanbahawateknik KMI merupakanteknik yangterbaikdalammembuat
pengekstrakan
imej ke atasimej kapalterbang.Peratusralat mutlakyangdiperolehi
daripadakajian ini ke ataskapalterbangberjenisAirbus A320-214ialahkurang
daripada0.0794iaitu mempunyaiketepatansebanyak99.92peratus.Teknik ini juga
sesuaidigunakanuntuk membuatanalisismengenaiciri-ciri intrakelasdaninterkelas.
Selainitu, bagipengelasan
imej didapatikaedahSOM dank-NearestNeighbour(kNN) sesuaidigunakanberdasarkan
nilai Percentageof CorrectClassffication(PCC)
yangtinggi bagi ketiga-tigasampeliaitu lebih daripada70 peratus.
v1
,
ABSRACT
Eyesarespecialgifts that aregivenby our Creator.Throughthemwe can
comprehendwhat happenedin the environment.Eyesact asa camerathat takesthe
particularof imageobjectsand sendit to the brainto be processed.Thus,researchers
areenthusiasticto invent a new machinethat mimickedhumanvision system.There
aretwo (2) significantphasesin the associated
systems;featureextractionand
classificationphase.In this research,three(3) momentinvarianttechniquesare
adoptedto performthe featureextractionof the aircraftimages,namelyLegendre
MomentInvariant(LMI), TchebichefMomentInvariant(TMI), andKrawtchouk
MomentInvariant(KMD. Self-Organising
Map (SOM)is usedto classi$the
resultingfeaturevectors. The resultfrom the resealchshowsthat KMI techniqueis
the bestfeatureextractiontechniquewhencomparedto the LMI andTMI. The
percentage
of absoluteerrorfor the featureextractionof an aircraftmodelAirbus
4320-214is leastthan 0.0794which is its accuracyis 99.92percent.Thusthe KMI
featuresvectorsareutilizedfor intraclass
andinterclass'analysis.
Besides,SOMand
k-NearestNeighbour(k-Itil.l)techniquearethe bestclassificationtechnique
(PCC). ThePCCfor the
accordingto percentage
of correctclassification
classification
of samplel,2,and 3 aremorethan7} percent.
60
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