Investigator: Wan-Chen Chan

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Abstract
Image registration is defined as the same object of two different sources alignment by some kind of image transformation. Since satellite imagery has different image types and complex image scenes for a variety of measurement observation, developing automatic image registration methods for satellite imagery is still a big challenge. Read more Improving Feature Point Matching Accuracy for Satellite Image Registration ›

Investigator: Wei-You Lin

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Abstract
According to recent research, stroke is one of the causes of death nationwide. Stroke is a disease of brain dysfunction caused by cerebral vascular occlusion or spontaneous rupture, which can be divided into ischemic and hemorrhagic. Both types of stroke lead to nutrient and oxygen deprivation in the brain, which ultimately cause brain damage or death. Read more Using Salient Region Detection and Deformable Models to Analyze Infarct Regions in Rat Brain Images ›

Investigator: Jun-Qi Li

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Abstract
In the field of undersea related research, underwater vehicles usually carry a visual system that captures various images of interested creatures, minerals and monitors environmental conditions. Unfortunately, the captured images often have serious color distortion and poor visibility problems. Read more Underwater Image Restoration Based on Multi-scale Fusion ›

Investigator: Ting-Ru Yang

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Abstract
Stroke is a disease of brain dysfunction caused by cerebral vascular occlusion or spontaneous rupture, which can be divided into ischemic and hemorrhagic. About 15 million people worldwide suffer from stroke every year. Of these, 5 million die and another 5 million are permanently disabled. Read more Using volumetric fluid registration techniques to assess infarct regions in rat brain MR images after stroke ›

Investigator: Hsiao-Fu Kuo

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Abstract
Stroke has the second highest fatality rate around the world. It can be divided into two major categories: ischemic and hemorrhagic. In the clinically, there is lots of development prospect. Rodents associated with magnetic resonance (MR) images are often preclinical experimental models. Researchers need to go through many processing steps before analyzing the operation, such as extracting the brain regions and infarct regions. Read more Infarct Region Segmentation in Rat Brain MR Images after Stroke Based on Convolutional Neural Networks ›

Investigator: Guan-Long Wu

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Abstract
Remote sensing image registration is still a challenging task because of the variety in image types and the lack of a consistent transformation. To improve image registration for remote sensing, a robust and accurate method is developed in this thesis. Read more An Accurate Feature Point Matching Algorithm for Automatic Remote Sensing Image Registration ›

Investigator: Yu-Hsuan Chao

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Abstract
Image registration is very important for a wide variety of image processing applications in engineering and medicine. It provides lots of precious information for further analysis in many fields. Image registration is the process of transforming different images into one coordinate system.
Read more Volumetric Medical Image Registration Using a Three Dimension Closed Incompressible Viscous Fluid Model ›

Investigator: Cheng-Yuan Li

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Abstract
This thesis proposes an effective noise reduction method for brain MR images. The proposed is based on the trilateral filter, which is a more powerful method than the bilateral filter in many cases. However, the computation of the trilateral filter is quite time-consuming and the choice of the filter parameters is also laborious. To address these problems, the trilateral filter algorithm is implemented using parallel computing with GPU. Subsequently, the optimal filter parameters are selected by artificial intelligence techniques. Read more Automatic Brain Magnetic Resonance Image Denoising Using A GPU-Based Trilateral Filter ›

Investigator: Chia-Yang Cheng

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Abstract
In the field of undersea research, underwater vehicles usually carry camera systems for recording. The captured images and videos often have two undesired characteristics: color distortion and low visibility. This is because that the light is exponentially attenuated while penetrating through water. Furthermore, the quantity of attenuation is associated with the wavelength of light spectrum. This thesis simplifies the Jaffe-McGlamery optical model and proposes an effective algorithm to recover underwater images. Read more Underwater Image Restoration by Red-Dark Channel Prior and Point Spread Function Deconvolution ›

Investigator: Chun-Hsiao Yeh

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Abstract
Face recognition has been extensively applied to a wide variety of security systems for identity authentication. However, due to the fact that the face info is particularly easy to access and reproduce, the vulnerability of security systems to spoofing face attacks (e.g., 2D printed photo, replayed video, 3D mask) is still an open security issue in the biometrics domain. In this thesis, an effective approach against face spoofing attacks based on perceptual image quality assessment features with multi-scale analysis is presented.
Read more Face liveness detection based on perceptual image quality assessment features with multi-scale analysis ›