Image pattern recognition with neural network

Microsoft PowerPoint Le Dung Image Pattern Recognition with Neural Network 11 2011 pptx h ê đề dà h h lớ hChuyên đề dành cho lớp cao học C IMAGE PATTERN RECOGNITIONIMAGE PATTERN RECOGNITION WITH NEURAL NETWORKWITH NEURAL NETWORKWITH NEURAL NETWORKWITH NEURAL NETWORK Dr Lê Dũngg School of Electronics and Telecommunications Hanoi University of Science and TechnologyHanoi University of Science and Technology Hà nội 112011ộ TABLE OF CONTENTTABLE OF CONTENT huyên đề dành cho lớp cao họcC 2 TABLE OF.

h ê đề dà dành h cho h lớ lớp cao học h Chuyên IMAGE PATTERN RECOGNITION WITH NEURAL NETWORK Dr Lê Dũng g School of Electronics and Telecommunications Hanoi University of Science and Technology Hà nội ộ 11/2011 C huyên đề dành cho lớp cao học TABLE OF CONTENT Part I: Design a real application using image pattern recognition with neural network Automatic Envelopes Classification System in the post office Skin color detector with Neural Network Part II: Image Pattern Recognition + Digital Image and Image Acquisition + Image Enhancement + Image I Segmentation S t ti + Image Pattern Recognition Part III: Recognition with Neural Network + Theory of Neural Network + Using Neural Network for Pattern Recognition HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY SCHOOL OF ELECTRONICS AND TELECOMMUNICATION C huyên đề dành cho lớp cao học MỤC TIÊU CỦA CHUYÊN ĐỀ ™ Hiểu “Mẫu Mẫu ảnh ảnh” (Image Pattern) nguyên lý nhận dạng mẫu ảnh (Image Pattern Recognition) ™ Nguyên tắc tạo chuẩn hóa mẫu ảnh phù hợp cho việc nhận dạng mạng Nơron Nơron ™ Nắm lý thuyết mạng Nơron nhận dạng mẫu ảnh Ỵ Định Đị h hướng h cho h việc iệ ứng ứ d dụng kỹ thuật th ật nhận hậ dạng mẫu ảnh mạng nơron HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY SCHOOL OF ELECTRONICS AND TELECOMMUNICATION C huyên đề dành cho lớp cao học TÀI LIÊU THAM KHẢO CHÍNH ‰ “Digital Image Processing” Barnd Jähne Spring Verlag 1995 ‰ “Neural Networks for Pattern Recognition” Bishop, C.M Oxford University Press, 1995 ‰ “Neural Network Design” Martin T Hagan, Howard B Demuth, Mark Beale Thomson Learning, 1996 ‰ “Gradient-based learning applied to document recognition” LeCun, Y., Bottou, L., Bengio, Y., Haffner, P Proceedings of the IEEE, IEEE vol vol 86, 86 1998 1998 HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY SCHOOL OF ELECTRONICS AND TELECOMMUNICATION C Part I : Design a real application huyên đề dành cho lớp cao học AUTOMATIC ENVELOPES CLASSIFICATION SYSTEM (Project : 010-2001-TCT-RDP-BC-26 at the Research Institute of Post and Telecommunication 2000-2001) Collected envelopes Control & Operation System Centre control Recognition result (postcode) Classification of envelope types Automatic Handwritten Postcode Recognition Image 640x480 Standard envelopes CCD camera Separate, p , Index & Put each of envelopes on conveyer belt Light My design control Mechanical System to classification Conveyer belt HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY SCHOOL OF ELECTRONICS AND TELECOMMUNICATION C Part I : Design a real application huyên đề dành cho lớp cao học DESIGN THE PROCESS OF FUNCTIONS Error (reject) Preprocessing Segmentation (Neural network) Image WxH CCD Camera Light xxxxx Recognition 28117 Classification OK Index i Envelope Multi-layers Feed-Forward Neural Network Conveyer belt ‹ Preprocessing ‹ Segmentation ‹ Recognition - Grayscale convert - Segment the postcode area - Enhancement - Segment g areas for - Binary convert each code number - Subtraction - Segment number patterns - Noise filter - Find envelope p frame - Rotate & Crop Postcode area HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY - Patterns normalization - Recognition using a neural network - Check result (OK or reject) SCHOOL OF ELECTRONICS AND TELECOMMUNICATION C Part I : Design a real application huyên đề dành cho lớp cao học NEURAL NETWORK FOR PATTERN RECOGNITION 16x16 Input layer Input layer : 256 Normalized Pattern 16x16 Layer 16 Activation function Log-Sigmoid a= 5x5 7x7 3x3 Layer : 106 (Feature map) 16 3x3 Layer 1 + e − n net 10 HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY Output layer Result Layer : 68 (Sub-sampling) Output layer : 10 (classification) Total : 440 neurons SCHOOL OF ELECTRONICS AND TELECOMMUNICATION C huyên đề dành cho lớp cao học Part I : Design a real application SOFTWARE MODULE (3) : RECOGNIZING POSTCODE HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY SCHOOL OF ELECTRONICS AND TELECOMMUNICATION C Part I : Design a real application huyên đề dành cho lớp cao học SKIN COLOR DETECTOR FOR A REAL-TIME HAND GESTURE RECOGNITION SYSTEM 2D Color Camera Skin color detector Skin color detection image Hand feature extraction Hand gesture recognition Hand tracking g Human-Robot interaction Human-Computer interaction HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY SCHOOL OF ELECTRONICS AND TELECOMMUNICATION C Part I : Design a real application huyên đề dành cho lớp cao học THE OVERVIEW OF MY COMBINING METHOD Step Step Image frame Result PRNN Collecting The statistical t ti ti l skin color model Training Building Training data set + Skin color patterns + Non-skin color patterns The originality of the method: Step 1: Using the statistical skin color model Ỉ Fast detection with not high accuracy (coarse work) Ỉ Check all pi pixels els of the image frame (coarse data) Step 2: Using the pattern recognition neural network Elliptical p skin color model Multi-layers FeedForward Neural Network ỈDetect with high accuracy (fine work) ỈL ỈLearn tto correctt th the ddetection t ti errors off the th statistical t ti ti l skin ki color l model d l HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY SCHOOL OF ELECTRONICS AND TELECOMMUNICATION 10 C Part I : Design a real application huyên đề dành cho lớp cao học DEFINE A PATTERN FOR SKIN COLOR PRNN* Non-skin Skin detection result based on the color information of a pixel ? Pattern for PRNN with pixels Skin Skin Non-skin Under examination pixel and its neighborhood pixels * PRNN – Pattern P R Recognition i i Neural N l Network N k HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY SCHOOL OF ELECTRONICS AND TELECOMMUNICATION 11 C Part I : Design a real application huyên đề dành cho lớp cao học TỔNG KẾT CÁC KHÁI NIỆM TRONG PHẦN I ¾ Khái niệm iệ mẫu ẫ ảnh ả h t nhận hậ dạng d ¾ Khái niệm tạo chuẩn hố mẫu ảnh ¾ Khái niệm ệ nhận ậ dạng g ¾ Khái niệm mạng nơron huấn luyện mạng nơron ¾ Khái niệm thư viện mẫu ảnh để huấn luyện ¾ Khái niệm huấn luyện mạng nơron HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY SCHOOL OF ELECTRONICS AND TELECOMMUNICATION 12 ... Image and Image Acquisition + Image Enhancement + Image I Segmentation S t ti + Image Pattern Recognition Part III: Recognition with Neural Network + Theory of Neural Network + Using Neural Network. .. application using image pattern recognition with neural network Automatic Envelopes Classification System in the post office Skin color detector with Neural Network Part II: Image Pattern Recognition. .. THAM KHẢO CHÍNH ‰ “Digital Image Processing” Barnd Jähne Spring Verlag 1995 ‰ ? ?Neural Networks for Pattern Recognition? ?? Bishop, C.M Oxford University Press, 1995 ‰ ? ?Neural Network Design” Martin