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Iris-segmentation
- 一篇主要介绍使用变量水平集方法进行虹膜分割的文章，之后也有其相应的归一化算法介绍以及特征提取及少部分的虹膜匹配-Introduced a level set method using the variable iris segmentation article, and then there are the corresponding normalization algorithm descr iption and a small number of feature extraction and
wavelet
- 介绍了小波变换的基本应用，采用小波滤波的方法实现对一组数据的处理，处理结果表明，选取合适的小波基函数以及分解层数才能够达到理想的效果-The basic application of wavelet transform, wavelet filtering method to achieve a set of data processing, processing results show that selecting the appropriate wavelet basis function
mit18086_levelset_front
- Level set method code
NCS2011---146---autmented-reality
- 目前擴增實境技術相關應用大部分以使用標記為主，但各式應用需求與日俱增，無標記(markerless)擴增實境技術使用上更具彈性，不必受限於標記的使用，因此應用層面更廣。視覺追蹤技術是擴增實境系統重要底層核心技術之一，但使用視覺追蹤技術在實際應用上易受到追蹤物件本身及外觀變化之影響，因此本文提出適用於無標記擴增實境應用之物件追蹤方法，能有效追蹤各式真實物件。首先框選設定追蹤物件；接著擷取物件特徵值，藉由特徵值比對以持續追蹤物件，並利用金字塔L-K光流法以縮短比對運算時間；最後經由2D-3D座標轉換
1-s2.0-S0895611110000157-main
- Computer-aided detection of multiple sclerosis lesions in brain magnetic resonance images: False positive reduction scheme consisted of rule-based, level set method, and support vector machine
1-s2.0-S016502701100522X-main_2
- The purpose of this study was to develop a computerized method for detection of multiple sclerosis (MS) lesions in brain magnetic resonance (MR) images. We have proposed a new false positive reduction scheme, which consisted of a rule-based metho