Call Number | T-1024 (Softcopy T-754) Source Code T-167 |
Collection Type | Tesis |
Title | Deteksi dan pengukuran biometri janin menggunakan AdaBoost Classifier dan Randomized Hough Transform |
Author | Zaki Imaduddin; |
Publisher | Depok: Fakultas Ilmu Komputer, 2013 |
Subject | Ultrasonography (USG), AdaBoost, Randomized Hough Transform |
Location | FASILKOM-UI; |
Nomor Panggil | ID Koleksi | Status |
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T-1024 (Softcopy T-754) Source Code T-167 | TERSEDIA |
ABSTRACT Nama : Zaki Imaduddin Program Studi : Ilmu Komputer Judul : Detection and Measurement of Fetal biometry using AdaBoost Classifier and Randomized Hough transform Ultrasonography (USG) is a diagnostic tool for detecting and analyzing organ structure in human body. One of the example usage of USG is to detect and analyze biometric features of a fetus. This study aims to detect and measure features of fetus from scanned image offetalhead (biparietal diameter) and femur length using ultrasound equipment. The detection and measurement process have several steps. It consists of cropping object and non-object, extracting features, selecting features, and measuring the fetal organs sizes. In this study, Haar-like feature is used to extract the feature meanwhile AdaBoost classifier is used for object detection and Randomized Hough Transform is applied for biometry measurement. In this research, we used 300 biparietal head image data and 200 image data of femur. After the data processing stage, we obtained the detection of biparietal as many as 44 images with an average error of 0.0388 and Correlation Coefficient result of 0,984, while the results for the detection of fetal femur error as many as 18 with an average of 0,554 and Correlation Coefficient result of 0,788. The result of this research can be optimized further to realize a fully integrated system that can detect and measure fetal organ with usable user interaction and affordable price. Keyword: Ultrasonography (USG), AdaBoost, Randomize Hough Transform