Archive for August, 2008

books that i need ! hoho $62.80…

Book Contents

1 Crunching Pixels
1.1 Programming with Images
1.2 Image Analysis and “Intelligent” Processing
2 Digital Images
2.1 Types of Digital Images
2.2 Image Acquisition
2.2.1 The Pinhole Camera Model
2.2.2 The “Thin” Lens
2.2.3 Going Digital
2.2.4 Image Size and Resolution
2.2.5 Image Coordinate System
2.2.6 Pixel Values
2.3 Image File Formats
2.3.1 Raster vs. Vector Images
2.3.2 Tagged Image File Format (TIFF)
2.3.3 Graphics Interchange Format (GIF)
2.3.4 Portable Network Graphics (PNG)
2.3.5 JPEG
2.3.6 Windows Bitmap (BMP)
2.3.7 Portable Bitmap Format (PBM)
2.3.8 Additional File Formats
2.3.9 Bits and Bytes
2.4 Exercises
3 ImageJ
3.1 Software for Digital Images
3.1.1 Software for Image Manipulation
3.1.2 Software for Image Processing
3.2 Properties of ImageJ
3.2.1 Features
3.2.2 Available Tools
3.2.3 ImageJ Plugins
3.2.4 An Example Plugin “inverter”
3.3 Additional Information about ImageJ and Java
3.3.1 ImageJ Resources
3.3.2 Programming with Java
3.4 Exercises
4 Histograms
4.1 What is a Histogram?
4.2 What can be discovered from a Histogram?
4.2.1 Brightness, Contrast, and Dynamic Range
4.2.2 Image Defects
4.3 Computing the Histogram
4.4 Histograms for Images with more than 8 bits
4.4.1 Binning
4.4.2 Example
4.4.3 Implementation
4.5 Histograms of Color Images
4.5.1 Intensity Histogram
4.5.2 Histogram of Individual Color Channels
4.5.3 Combined Color Histogram
4.6 Cumulative Histogram
4.7 Exercises
5 Point Operations
5.1 Changing Pixel Intensity
5.1.1 Contrast and Brightness
5.1.2 Clamping
5.1.3 Automatic Contrast Enhancement
5.1.4 Inverting Images
5.1.5 Thresholding
5.1.6 Point Operations and Histograms
5.2 Linear Histogram Equalization
5.2.1 Histogram Specification
5.3 Gamma Correction
5.3.1 Why Gamma?
5.3.2 The Gamma Function
5.3.3 Real Gamma Values
5.3.4 Applying Gamma Correction
5.3.5 Implementation
5.3.6 Gamma Function with Offset
5.4 Point Operations in ImageJ
5.4.1 Point Operations with Look-up Tables
5.4.2 Standard Arithmetic Operations
5.4.3 Point Operations with Multiple Images
5.4.4 ImageJ Plugins for Multiple Images
5.5 Exercises
6 Filters
6.1 What is a Filter?
6.2 Linear Filters
6.2.1 The Filter Matrix
6.2.2 Using Filters
6.2.3 Computing Filter Operations
6.2.4 Filter Plugin Example
6.2.5 Integer Coefficients
6.2.6 Arbitrary Size Filters
6.2.7 Types of Linear Filters
6.3 Formal Properties of Linear Filters
6.3.1 Linear Convolution
6.3.2 Properties of Linear Convolution
6.3.3 Separability of Filters
6.3.4 Impulse Response
6.4 Non-linear Filters
6.4.1 Minimum- and Maximum-Filter
6.4.2 Median Filter
6.4.3 The Weighted Median Filter
6.4.4 Additional Non-linear Filters
6.5 Filter Implementation
6.5.1 Efficiency of Filter Programs
6.5.2 Handling Image Borders
6.6 Filter Operations in ImageJ
6.6.1 Linear Filters
6.6.2 Gaussian Filters
6.6.3 Non-linear Filters
6.7 Exercises
7 Edges and Contours
7.1 How do Edges Arise
7.2 Gradient Based Edge Detection
7.2.1 Partial Derivatives and the Gradient
7.2.2 Derivative Filters
7.3 Filters for Edge Detection
7.3.1 Prewitt and Sobel Operators
7.3.2 Roberts Operator
7.3.3 Compass Operators
7.3.4 Edge Operators in ImageJ
7.4 Additional Edge Operators
7.4.1 Edge Detection with Second Derivatives
7.4.2 Edges at Different Scales
7.4.3 Canny Filter
7.5 From Edges to Contours
7.5.1 Contour Following
7.5.2 Edge Images
7.6 Edge Enhancement
7.6.1 Edge Enhancement using the Laplace Filter
7.6.2 Unsharp Masking
7.7 Exercises
8 Finding Points of Interest
8.1 Points of Interest
8.2 Harris Corner Detector
8.2.1 Local Structure Matrix
8.2.2 Corner Response Function (CRF)
8.2.3 Determining Corner Points
8.2.4 Example
8.3 Implementation
8.3.1 Step 1 – Computing the Corner Response Function
8.3.2 Step 2 – Determining the Corner Points
8.3.3 Displaying the Corner Points
8.3.4 Summary
8.4 Exercises
9 Detecting Simple Curves
9.1 Salient Structures
9.2 Hough Transform
9.2.1 Parameter Spaces
9.2.2 Accumulator Array
9.2.3 A Better Representation for Lines
9.3 Implementing the Hough Transform
9.3.1 Filling the Accumulator Array
9.3.2 Analyzing the Accumulator Array
9.3.3 Extensions to the Hough Transform
9.4 Hough Transforms for Circles and Ellipses
9.4.1 Circles and Arcs
9.4.2 Ellipses
9.5 Exercises
10 Morphological Filters
10.1 Shrinking and Growing
10.1.1 Image Neighborhoods
10.2 Basic Morphological Operations
10.2.1 The Structuring Element
10.2.2 Point Sets
10.2.3 Dilation
10.2.4 Erosion
10.2.5 Properties of Dilation and Erosion
10.2.6 Design of Morphological Filters
10.2.7 Example Usage: Outlining
10.3 Composite Operations
10.3.1 Opening
10.3.2 Closing
10.3.3 Properties of Opening and Closing
10.4 Morphological Filters for Grayscale and Color Images
10.4.1 Structuring Elements
10.4.2 Grayscale Dilation and Erosion
10.4.3 Grayscale Opening and Closing
10.5 Implementing Morphological Filters
10.5.1 Binary Images in ImageJ
10.5.2 Dilation and Erosion
10.5.3 Opening and Closing
10.5.4 Outlining
10.5.5 Morphological Operations in ImageJ
10.6 Exercises
11 Regions in Binary Images
11.1 Finding Image Regions
11.1.1 Region Marking with Flood Filling
11.1.2 Sequential Region Marking
11.1.3 Region Marking – Summary
11.2 Region Contours
11.2.1 Internal and External Contours
11.2.2 Combining Region Marking and Contour Finding
11.2.3 Implementation
11.2.4 Example
11.3 Representing Image Regions
11.3.1 Matrix Representation
11.3.2 Run Length Encoding
11.3.3 Chain Codes
11.4 Properties of Binary Regions
11.4.1 Shape Features
11.4.2 Geometric Properties
11.4.3 Statistical Shape Properties
11.4.4 Moment Based Geometrical Properties
11.4.5 Projections
11.4.6 Topological Properties
11.5 Exercises
12 Color Images
12.1 RGB Color Images
12.1.1 Organization of Color Images
12.1.2 Color Images in ImageJ
12.2 Color Spaces and Color Conversion
12.2.1 Conversion to Grayscale
12.2.2 Color Image De-saturation
12.2.3 HSV/HSB and HLS Color Spaces
12.2.4 TV Component Color Spaces – YUV, YIQ, YCbCr
12.2.5 Color Space for Printing – CMY and CMYK
12.3 Colorimetric Color Spaces
12.3.1 CIE Color Space
12.3.2 CIE L*a*b*
12.3.3 sRGB
12.3.4 Adobe RGB
12.3.5 Colors and Color Spaces in Java
12.4 Color Image Statistics
12.4.1 How many Colors are in an Image?
12.4.2 Histograms
12.5 Color Quantization
12.5.1 Scalar Color Quantization
12.5.2 Vector Quantization
12.6 Exercises
13 Introduction to Spectral Techniques
13.1 The Fourier Transform
13.1.1 Sine and Cosine Functions
13.1.2 Representing Periodic Functions with Fourier Series
13.1.3 The Fourier Transform
13.1.4 Fourier Transform Pairs
13.1.5 Important Properties of the Fourier Transform
13.2 Transition to Discrete Data
13.2.1 Sampling
13.2.2 Discrete and Periodic Functions
13.3 The Discrete Fourier Transform (DFT)
13.3.1 Definition of the DFT
13.3.2 Discrete Basis Functions
13.3.3 Yet Again Aliasing!
13.3.4 Units in Spatial and Spectral Spaces
13.3.5 The Power Spectrum
13.4 Implementation of the DFT
13.4.1 Direct Implementation
13.4.2 Fast Fourier Transform (FFT)
13.5 Exercises
14 The Discrete Fourier Transform in 2D
14.1 Definition of the 2D DFT
14.1.1 2D Basis Functions
14.1.2 Implementing the 2D DFT
14.2 Representing the Fourier Transform in 2D
14.2.1 Range of Values
14.2.2 Centered Representation
14.3 Frequency and Orientation in 2D
14.3.1 Effective Frequency
14.3.2 Frequency Limits and Aliasing in 2D
14.3.3 Orientation
14.3.4 Geometric Correction of the 2D Spectrum
14.3.5 Effects of Periodicity
14.3.6 Windowing
14.3.7 Windowing Functions
14.4 2D Fourier Transform Examples
14.5 Properties of the DFT
14.5.1 Linear Filter Operations in the Spectral Domain
14.5.2 Linear Convolution and Correlation
14.5.3 Inverse Filters
14.6 Exercises
15 The Discrete Cosine Transform (DCT)
15.1 One Dimensional DCT
15.1.1 DCT Basis Functions
15.1.2 Implementing the One Dimensional DCT
15.2 Two Dimensional DCT
15.2.1 Separability
15.2.2 Example
15.3 Additional Spectral Transformations
15.4 Exercises
16 Geometrical Image Operations
16.1 Coordinate Transformations in 2D
16.1.1 Simple Transformations
16.1.2 Homogeneous Coordinates
16.1.3 Affine Transformations (Three Point Transformations)
16.1.4 Projective Transformations (Four Point Transformations)
16.1.5 Bilinear Transformations
16.1.6 Additional Non-Linear Image Deformations
16.2 Re-Sampling
16.2.1 Source-to-Target Mapping
16.2.2 Target-to-Source Mapping
16.3 Interpolation
16.3.1 Simple Interpolation Methods
16.3.2 Ideal Interpolation
16.3.3 Interpolation Using Convolution
16.3.4 Cubic Interpolation
16.3.5 Interpolation in 2D
16.3.6 Aliasing
16.4 Java Implementation
16.4.1 Geometrical Transformations
16.4.2 Pixel Interpolation
16.4.3 Usage Example
16.5 Exercises
17 Image Comparison
17.1 Template Matching in Intensity Images
17.1.1 Distance between Image Patterns
17.1.2 Dealing with Rotation and Scale Changes
17.1.3 Implementation
17.2 Comparison of Binary Images
17.2.1 Direct Comparison of Binary Images
17.2.2 The Distance Transform
17.2.3 Chamfer Matching
17.3 Exercises
A Mathematical Notation
A.1 Often Used Symbols
A.2 Complex Numbers C
A.3 Algorithmic Complexity and O Notation
B Java Notes
B.1 Arithmetic
B.1.1 Integer Division
B.1.2 Modulus Operator
B.1.3 Unsigned Bytes
B.1.4 Mathematical Functions (Math-Class)
B.1.5 Rounding
B.1.6 Inverse Tangent Function
B.1.7 Float and Double (Classes)
B.2 Arrays in Java
B.2.1 Creating Arrays
B.2.2 Size of Arrays
B.2.3 Access to Array Elements
B.2.4 Two Dimensional Arrays
C ImageJ Short Reference
C.1 Installation and Setup
C.2 ImageJ API
C.2.1 Images (Package ij)
C.2.2 Image Processing (Package ij.process)
C.2.3 Plugins (Packages ij.plugin, ij.plugin.filter)
C.2.4 GUI Classes (Package ij.gui)
C.2.5 Window Management (Package ij)
C.2.6 Utility Classes (Package ij)
C.2.7 Input-Output (Package ij.io)
C.3 Image and Image Stacks Creation
C.3.1 ImagePlus (Class)
C.3.2 ImageStack (Class)
C.3.3 NewImage (Class)
C.3.4 ImageProcessor (Class)
C.4 Image Processor Creation
C.4.1 ImageProcessor (Class)
C.4.2 ByteProcessor (Class)
C.4.3 ColorProcessor (Class)
C.4.4 FloatProcessor (Class)
C.4.5 ShortProcessor (Class)
C.5 Image Parameters
C.5.1 ImageProcessor (Class)
C.6 Accessing Pixels
C.6.1 ImageProcessor (Class)
C.7 Converting from Images
C.7.1 ImageProcessor (Class)
C.7.2 ImagePlus, ImageConverter (Classes)
C.8 Histogram and Image Statistics
C.8.1 ImageProcessor (Class)
C.9 Point Operations
C.9.1 ImageProcessor (Class)
C.9.2 Blitter (Interface)
C.10 Filter
C.10.1 ImageProcessor (Class)
C.11 Geometrical Operations
C.11.1 ImageProcessor (Class)
C.12 Graphical Operations on Images
C.12.1 ImageProcessor (Class)
C.13 Displaying Images
C.13.1 ImagePlus (Class)
C.14 Image Stack Operations
C.14.1 ImagePlus (Class)
C.14.2 ImageStack (Class)
C.14.3 Stack Example
C.15 Region of Interest (ROI)
C.15.1 ImageProcessor (Class)
C.15.2 ImageStack (Class)
C.15.3 ImagePlus (Class)
C.15.4 Roi, Line, OvalRoi, PolygonRoi (Classes)
C.16 Image Properties
C.16.1 ImagePlus (Class)
C.17 Interaction
C.17.1 IJ (Class)
C.17.2 ImageProcessor (Class)
C.17.3 GenericDialog (Class)
C.18 Plugins
C.18.1 PlugIn(Interface)
C.18.2 PlugInFilter(Interface)
C.18.3 Executing Plugins
C.19 Window Management
C.19.1 WindowManager (Class)
C.20 Additional Functions
C.20.1 ImagePlus (Class)
C.20.2 IJ (Class)
D Source Code
D.1 Harris Corner Detector
D.1.1 File Corner.java
D.1.2 File HarrisCornerDetector.java
D.1.3 File HarrisCornerPlugin_.java
D.2 Combined Region Marking and Contour Following
D.2.1 File ContourTracingPlugin_.java
D.2.2 File Node.java
D.2.3 File Contour.java
D.2.4 File OuterContour.java
D.2.5 File InnerContour.java
D.2.6 File ContourSet.java
D.2.7 File ContourTracer.java
D.2.8 File ContourOverlay.java

hmm…. think twice? think trice? hahah?
may be i should find in torrent for this book ..ngeh2
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Stage One – Case Study: JImage

salams..

hmm.. since i had go through the experiment stage.. i had to find out the tools needed for the system requirement …by using ” Digital image + Java ” Keyword..alhamdulillah i had flooded  resources..now is time to choose and read the most related information..insyaallah..

my target for this week is make quick case study about JImage and re-flow my flow chart …

I had found the similar prototype with mine .. nVivo.. the qualitative research tools application ..hmm.. i still try to understand how the implementation of character regonition was done here..hoho…

Insyaallah by in the middle of August I am clear with my system.

The system analysis is the most important part. The precise analysis will help much in the development stage 🙂

Ya Allah, may i faced all circumstances smoothly ameen…

Alhamdulillah, in the experiment stage ^_^|| huhu!

Alhamdulillah, my status now is the experiment stage … hoho I have 3 month to build the prototype from my research algorithm. Caiyoks !