IMPLEMENTASI SENSOR KAMERA KINECT UNTUK MENGUKUR PANJANG OBJEK BENDA MENGGUNAKAN METODE ITERATIVE CLOSEST POINT
Tugas Akhir
Sebagai Persyaratan Guna Meraih Gelar Sarjana Strata 1 Teknik Informatika Universitas Muhammadiyah Malang
disusun oleh:
Disusun oleh : ANDIK RAMADHANI (09560283)
Program Studi Teknik Informatika Fakultas Teknik Universitas Muhammadiyah Malang 2013
KATA PENGANTAR
Dengan memanjatkan puji syukur kehadirat Allah SWT. Atas limpahan rahmat dan hidayah-Nya sehingga peneliti dapat menyelesaikan tugas akhir yang berjudul : “IMPLEMENTASI SENSOR KAMERA KINECT UNTUK MENGUKUR PANJANG OBJEK BENDA MENGGUNAKAN METODE ITERATIVE CLOSEST POINT”
Di dalam tulisan ini disajikan pokok-pokok bahasan yang meliputi tentang implementasi sensor kamera kinect untuk mengukur panjang objek benda menggunakan metode iterative closest point. Aplikasi yang dibuat diharapkan dapat membantu mempermudah user untuk mengukur panjang objek benda. Peneliti menyadari sepenuhnya bahwa dalam penulisan tugas akhir ini masih banyak kekurangan dan keterbatasan.
Oleh karena itu peneliti
mengharapkan saran yang membangun agar tulisan ini bermanfaat bagi perkembangan ilmu pengetahuan kedepan.
Malang, 15 Juli 2013
Penulis
DAFTAR ISI
ABSTRAK ...............................................................................................
i
LEMBAR PERNYATAAN ......................................................................
ii
LEMBAR PERSETUJUAN ......................................................................
iii
LEMBAR PENGESAHAN .......................................................................
iv
KATA PENGANTAR ..............................................................................
v
DAFTAR ISI ............................................................................................
vi
DAFTAR GAMBAR ................................................................................
viii
DAFTAR TABEL .....................................................................................
x
DAFTAR PUSTAKA ...............................................................................
xi
BAB I PENDAHULUAN .........................................................................
1
1.1 Latar Belakang ........................................................................
1
1.2 Rumusan Masalah ...................................................................
2
1.3 Batasan Masalah ......................................................................
2
1.4 Tujuan Penelitian .....................................................................
2
1.5 Metodologi Pengerjaan ............................................................
2
1.5.1 Studi Pustaka ..................................................................
3
1.5.2 Merancang Desain Sistem ...............................................
3
1.5.3 Implementasi Sistem .......................................................
3
1.5.4 Pengujian dan Analisa .....................................................
3
1.5.5 Penyusunan Laporan .......................................................
3
1.6 Sistematika Penulisan ..............................................................
4
BAB II LANDASAN TEORI ...................................................................
5
2.1 Microsoft Kinect .....................................................................
5
2.1.1 Sensor Depth Of Kinect ................................................
6
2.2 Iterative Closest Point .............................................................
7
2.2.1 Selection Sample Point ...................................................
7
2.2.2 Matching to Point............................................................
8
2.2.3 Weighting and correspondences ......................................
8
2.2.4 Rejecting Certain (outlier) Point Pairs .............................
8
2.2.5 Meminimalisi kesalahan matrik dalam tranformasi..........
9
2.3 Point Clouds ........................................................................... 10 2.4 Software Development Kit (SDK) .......................................... 14 2.5 Kinect Developer Toolkit ....................................................... 15
BAB III ANALISA DAN PERANCANGAN SISTEM ............................. 16 3.1 Analisis Sistem ..................................................................... 16 3.1.1 Software dan Hardware ................................................ 16 3.1.2 Analisis Masalah .......................................................... 17 3.2 Arsitektur Sistem .................................................................. 18 3.3 Perancangan Proses .............................................................. 19 3.3.1 Flowchart ..................................................................... 19 3.4 Perancangan Interface .......................................................... 22 3.5 Perancangan Pengujian ......................................................... 23 3.5.1 Metode Pengujian ........................................................ 23 3.5.2 Parameter Pengujian .................................................... 23
BAB IV IMPLEMENTASI DAN PENGUJIAN ....................................... 25 4.1 Implementasi ......................................................................... 25 4.1.1 Implementasi Sistem ..................................................... 25 4.2 Pengujian ............................................................................. 30 4.2.1 Pengujian Iterative Closest point dan Point Cloud ......... 30 4.2.2 Pengujian Terhadap Cahaya .......................................... 31 4.2.3 Pengujian panjang objek berdasar jarak ........................ 32 4.2.4 Pengujian terhadap warna backgroun ............................ 35 4.3 Hasil Pengujian...................................................................... 36
BAB V PENUTUP .................................................................................... 39 5.1 Kesimpulan ............................................................................ 39 5.2 Saran ...................................................................................... 40
DAFTAR GAMBAR
Gambar 2.1 Kamera Kinect ......................................................................
5
Gambar 2.2 Sensor-sensor yang dimiliki kinect ........................................
6
Gambar 2.3 Range Image Registration .....................................................
7
Gambar 2.4 Closest Point dan Point to Plane ............................................
9
Gambar 2.5 Rekonstruksi Point Cloud ....................................................
10
Gambar 2.6 Rekonstruksi Kelinci ............................................................
11
Gambar 2.8 Proses Point Cloud ................................................................
12
Gambar 2.9 Microsoft Kinect SDK ..........................................................
14
Gambar 3.0 Kinect Developer Toolkit ......................................................
15
Gambar 3.1 Arsitektur Sistem ..................................................................
18
Gambar 3.2 Flowchart Sistem ..................................................................
19
Gambar 3.3 Rekonstruksi Point Cloud with kinect SDK ...........................
20
Gambar 3.4 Hasil registrasi Iterative Closest Point ...................................
21
Gambar 3.5 Desain Sistem .......................................................................
22
Gambar 4.1 Library SDK yang digunakan ................................................
25
Gambar 4.2 Library Tambahan ................................................................
26
Gambar 4.3 Penggunaan Class DepthImageFrameReady .........................
26
Gambar 4.4 Penggunaan DirectionalLight ...............................................
27
Gambar 4.5 Penggunaan GeometryModel3D ..........................................
27
Gambar 4.6 Penggunaan Enumeration ColorImageFormat .......................
28
Gambar 4.7 Penggunaan Metode ICP ......................................................
29
Gambar 4.8 Penggunaan Marker .............................................................
29
Gambar 4.9 Tampilan point cloud dan iterative closest point ...................
30
Gambar 4.10 Rekonstruksi objek benda pada cahaya yang redup ..............
31
Gambar 4.11 Rekonstruksi objek benda pada cahaya yang cukup...............
31
Gambar 4.12 Percobaan pengukuran dari jarak 80 cm ................................
33
Gambar 4.13 Percobaan pengukuran dari jarak 900 cm ..............................
33
Gambar 4.14 Percobaan pengukuran dari jarak 100 cm ..............................
34
Gambar 4.15 Percobaan pengukuran dari jarak 110 cm ..............................
34
Gambar 4.16 Percobaan pengukuran dari jarak 120 cm ..............................
35
Gambar 4.17 Percobaan warna backgorund yang sama dengan objek ........
35
Gambar 4.18 Percobaan warna objek yang berbeda dengan backgorund ....
36
Daftar pustaka
[1] Rendi Budiman, Imam Kuswardayan, dan Dwi Sunaryono.2012. Integrasi Kinect dan Unreal Development kit menggunakan Kerangka Kerja Open NI Pada studi kasus game berbasis interaksi gerakan, Jurusan Teknik Informatika, Fakultas Teknologi Informasi, Institut Teknologi Sepuluh Nopember (ITS).
[2] Meidya Koeshardianto1), Eko Mulyanto2), Moch. Hariadi3).2011. Registrasi Permukaan Obyek Tiga Dimensi Menggunakan Fitur Angular Invariant
Modified,
1)Jurusan
Teknik
Informatika,
Fakultas
Teknik,Universitas Trunojoyo, 2,3)Jurusan Teknik Elektro, Fakultas Teknologi Industri, Institut Teknologi Sepuluh Nopember.
[3] Ronen Gvili ,Iterative Closest Point. [4] Lena Maier-Hein, Alfred M. Franz, Thiago R. dos Santos, Mirko Schmidt, Markus Fangerau, Hans-Peter Meinzer, and J. Michael Fitzpatrick.2012. Convergent Iterative Closest-Point Algorithm to Accomodate Anisotropic and Inhomogenous Localization Error, Fellow, IEEE.
[5] Dr. Francis Colas.2011. Iterative Closest Point Algorithm,ETH Zurich.
[6] Juha Hyvärinen.2012. Surface Reconstruction Of Point Clouds Capture With Microsoft Kinect, Technology and Telecommunications Oulu University of Applied Sciences.
[7] Xingyan Li, Ian Yen-Hung Chen, Stephen Thomas, Bruce A MacDonald. 2012. Using Kinect for monitoring warehouse order picking operations, Department of Electrical and Computer Engineering, University of Auckland, New Zealand.
[8] M.R. Andersen, T. Jensen, P. Lisouski, A.K. Mortensen, M.K. Hansen,T. Gregersen and P. Ahrendt.2012. Kinect Depth Sensor Evaluation For Computer Vision Applications, Department of Engineering – Electrical and Computer Engineering, Aarhus University.
[9] Autumn Term.2010, Recent Development of the Iterative Closest Point (ICP) Algorithm, ETH zurich.
[10] Mien Hendry.2013. Membangun Aplikasi Menggambar 2 Dimensi Memanfaatkan 3 dimensi depth of kinect dengan menggunakan metode skeleton tracking, Universitas Muhammadiyah Malang.
