An Introduction to Pattern Recognition主講人：朱家德 • 財團法人資訊工業策進會(III) • 網路多媒體研究所
大綱 • Introduction • Image Processing • Feature Extraction and Selection Methods • Biometrics Recognition • Research and Development Results
Introduction 財團法人資訊工業策進會(III) 網路多媒體研究所(NMI)
What is Pattern Recognition • Definition: The act of taking in raw data and making an action based on the “category” of the pattern. • What is the pattern? The pattern is a picture, a string of characters, a set of symbols, a sequence of signal, etc.
Pattern Recognition • Example The optical sensing is used to automate the process of sorting fish
Machine Perception Face Recognition Character Recognition Computer Aid Diagnosis Speech Recognition
Examples of Application • Handwritten: sorting letters by postal code, input device for PDA‘s. • Printed texts: reading machines for blind people, digitalization of text documents. • Optical Character Recognition (OCR) • Biometrics • Diagnostic systems • Military applications • Face recognition. • Fingerprints recognition. • Speech recognition. • Medical diagnosis: X-Ray, ECG analysis. • Machine diagnostics, waster detection. • Automated Target Recognition (ATR). • Image segmentation and analysis (recognition from aerial or satelite photographs).
Image Processing 財團法人資訊工業策進會(III) 網路多媒體研究所(NMI)
What is image processing • Two main application areas: 1.Improvement of pictorial information 2.Processing of image data for storage, transmission and feature extraction for machine perception.
2-D Image Model • The 2-D image has a two-dimensional light intensity function f(x,y), where x and y denote spatial coordinates and the value is proportional to the brightness of the image at that point.
2-D Image Model • In the black and white case, the brightness value are called gray levels(灰階). These values are integer, non-negative, and bounded. • The elements of f(x,y) are called pixels being commonly used abbreviations of “picture elements”. • A digital image is an image f(x,y) which has been discretized both in spatial coordinates and brightness. An image can be considered as a matrix whose row and column indices identify a pixel in the image and the corresponding matrix element value identifies the gray level at that pixel.
Image type Color 彩色影像 • Gray 灰階影像 800x600x3=1440000 pixels 800x600=480000 pixels 每個pixel是由三個値組成 (R, G, B) 每個pixel是由一個値組成
Image Enhancement • Contrast Enhancement(增強對比)
Noise removing • 去除影像中在影像處理過程所造成的雜訊
Image Smoothing • 去除影像中因不良取像或量化所造成的雜訊,同時也會使影像變模糊
Image Sharpening • 強化影像中物體的邊緣效果
Effects of sampling • Human visual and audio perception is insensitive to high frequency information. • Telephone system provides sound frequencies to 3 KHz. Human hearing goes up to 20 KHz.
Effects of sampling 128x128 256 x 256 64x64 32x32
Feature Extraction and Selection Methods 財團法人資訊工業策進會(III) 網路多媒體研究所(NMI)
Feature Extraction and Selection Methods Task: to extract features which are good for classification. Good features: • Objects from the same class have similar feature values. • Objects from different classes have different values. “Good” features “Bad” features
Biometric Recognition 財團法人資訊工業策進會(III) 網路多媒體研究所(NMI)
Password Limitations • 傳統身分認證方法 - key • license or card • password • and so on • 缺點 • Stolen • Lost • Forgotten(too many or hard to memorize) • Misplaced
What is Biometric Recognition? • The biometrics recognition is the process of automatically differentiating people on the basis of individuality information from their physical or behavioral characteristics like fingerprint, iris, face, voice, and etc.