'Gray values' diaporamas de présentation

Introduction

Introduction. TOPIC 6 Image Enhancement. What are Image Features?. Local, meaningful, detectable parts of the image. More Color Woes. Squares with dots in them are the same color. Topics. Image Enhancement Brightness mapping Contrast stretching/enhancement Histogram modification

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Feature Extraction

Feature Extraction. CSC 59866CD Fall 2004. Lecture 7 Image Enhancement. Zhigang Zhu, NAC 8/203A http://www-cs.engr.ccny.cuny.edu/~zhu/ Capstone2004/Capstone_Sequence2004.html. What are Image Features?. Local, meaningful, detectable parts of the image. More Color Woes.

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Introduction

Introduction. CSc I6716 Spring 2012. Part I Feature Extraction (1). Image Enhancement. Zhigang Zhu, City College of New York zhu@cs.ccny.cuny.edu. What are Image Features?. Local, meaningful, detectable parts of the image. More Color Woes. Squares with dots in them are the same color.

784 views • 71 slides

Introduction

Introduction. CSc I6716 Fall 2009. Part I Feature Extraction (1). Image Enhancement. Zhigang Zhu, City College of New York zhu@cs.ccny.cuny.edu. What are Image Features?. Local, meaningful, detectable parts of the image. More Color Woes. Squares with dots in them are the same color.

813 views • 71 slides

Introduction

Introduction. CSc I6716 Fall 2010. Part I Feature Extraction (1). Image Enhancement. Zhigang Zhu, City College of New York zhu@cs.ccny.cuny.edu. What are Image Features?. Local, meaningful, detectable parts of the image. More Color Woes. Squares with dots in them are the same color.

769 views • 71 slides

Introduction

Introduction. CSc I6716 Spring 2008. Part I Feature Extraction (1). Image Enhancement. Zhigang Zhu, City College of New York zhu@cs.ccny.cuny.edu. What are Image Features?. Local, meaningful, detectable parts of the image. More Color Woes. Squares with dots in them are the same color.

779 views • 71 slides

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Face recognition: component-based versus global approaches

Face recognition: component-based versus global approaches. ???? : ??? ?? ???? : ??? ???? : 2010/10/08. ????. Computer Vision and Image Understanding Volume 91, Issues 1-2 , July-August 2003, Pages 6-21 Special Issue on Face Recognition Authors :

616 views • 48 slides

L24. More on Image File Processing

L24. More on Image File Processing. Filtering Noise Edge Detection. Pictures as Arrays. A black and white picture can be encoded as a 2D Array Typical: 0 <= A(i,j) <= 255 (black) (white) Values in between correspond to different

555 views • 45 slides

L24. More on Image File Processing

L24. More on Image File Processing. Filtering Noise Edge Detection. Pictures as Arrays. A black and white picture can be encoded as a 2D Array Typical: 0 <= A(i,j) <= 255 (black) (white) Values in between correspond to different

551 views • 45 slides

Chapter 3. Intensity Transformation and Spatial Filtering

Chapter 3. Intensity Transformation and Spatial Filtering. This Session will cover : What is image enhancement Basic Intensity Transformation Functions (Enhancement overview) Histogram Processing. Center for Artificial Intelligence and RObotics (CAIRO). What is Image Enhancement?.

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Image Processing

Image Processing. Image Processing. a typical image is simply a 2D array of color or gray values i.e., a texture image processing takes as input an image and outputs characteristics about the image a new image modifies the input image

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Manipulating contrast/point operations

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