... dotplot before
convolution; and (b) after convolution.
2.3 Convolution and local edge detection
Convolution is the method of choice for enhancing
and detecting the edges in an image. For noise ... 1996). This paper presents a
new approach based on imageprocessing (IP)
techniques, which is immune to such predicaments.
2. BCP as imageprocessing
2.1 Estimation of LTP
A wide variety of ... Hough transform always detect the most
apparent line segments even in a noisy dotplot.
Before applying Hough transform, the same
processes of normalization and thresholding are
performed first....
... xix
1
Introduction 15
1.1 What Is DigitalImage Processing? 15
1.2 The Origins of DigitalImageProcessing 17
1.3 Examples of Fields that Use DigitalImageProcessing 21
1.3.1 Gamma-Ray Imaging ... Used 34
1.4 Fundamental Steps in DigitalImageProcessing 39
1.5 Components of an ImageProcessing System 42
Summary 44
References and Further Reading 45
2
Digital Image Fundamentals 34
2.1 Elements ... Pseudocolor ImageProcessing 302
6.3.1 Intensity Slicing 303
6.3.2 Gray Level to Color Transformations 308
6.4 Basics of Full-Color ImageProcessing 313
6.5 Color Transformations 315
6.5.1 Formulation...
... overlap be-
tween imageprocessing and image analysis is the area of recognition of indi-
vidual regions or objects in an image. Thus, what we call in this book digital
imageprocessing encompasses ... processing on images involves
tasks such as segmentation (partitioning an image into regions or objects),
description of those objects to reduce them to a form suitable for computer
processing, ... the digital computer. In fact,
digital images require so much storage and computational power that progress
in the field of digitalimageprocessing has been dependent on the development
of digital...
...
Digital ImageProcessing – Part II
54
Morphological Image Processing
(a)
(c)
(d)
(b)
Digital ImageProcessing – Part II
87
Image Segmentation
(a) (b)
(c)
(a)
(b)
Digital Image ... between two image objects is represented by a special neighbour
link object. The image is partitioned by image objects; all image objects of such a partition are called an
image object level. ... The image
objects of any level are restricted to be completely included (according to their associated image regions)
in some imageobject on any “higher order” imageobject level. The image object...
... Discriminative Models forObject Detection
Our aim is to take an n × m image x and infer a label for each pixel indicating
the class of object that pixel belongs to. We denote the set of all image pixels ... degrees.
Detecting Multiple Objects: Our model assumes that a single object is
present in the image. We can reject images with no objects by comparing the
evidence for this model with the evidence for a background-only ... single object in the image (although it can be used recursively for detecting
multiple objects – see Section 4).
We define a conditional model for the label image y,thepositionT , the part
image...
... Edge Detection 379
10.1.1 Point Detection 379
10.1.2 Line Detection 381
10.1.3 Edge Detection Using Function
edge 384
10.2 Line Detection Using the Hough Transform 393
10.2.1 Hough Transform ... acquiring an image of the area containing the text, preprocessing
that image, extracting (segmenting) the individual characters, describing the
characters in a form suitable for computer processing, ... deals with pseudocolor and
full-color image processing. Color models applicable to digitalimage process-
ing are discussed, and IPT functionality in color processing is extended via im-
plementation...
... histogram of a given image. However, once the
transformation function for an image has been computed, it does not change
annotation
See the help page for this
function for details on
how to ... illustrate MATLAB
formulations representative of processingtechniques in these two categories.
We also introduce the concept of fuzzy imageprocessing and develop sever-
al new M-functions for their ... addition, T can operate on a set of images, such as performing the addition
of K images for noise reduction.
3.3 ■ Histogram Processing and Function Plotting 97
described for function bar. If horz is...
... respectively, of an object. Then, for a transmissive object, the
observed light spectral energy distribution is
(2.1-1)
E λ()
t λ() r λ()
C λ() t λ()E λ()=
Digital Image Processing: PIKS Inside, ... ImageDetection and Registration 613
19.1 Template Matching, 613
19.2 Matched Filtering of Continuous Images, 616
19.3 Matched Filtering of Discrete Images, 623
19.4 Image Registration, 625
DIGITAL ... York
•
Chichester
•
Weinheim
•
Brisbane
•
Singapore
•
Toronto
CONTENTS
xi
PART 6 IMAGEPROCESSING SOFTWARE 641
20 PIKS ImageProcessing Software 643
20.1 PIKS Functional Overview, 643
20.2 PIKS Core Overview, 663
21 PIKS ImageProcessing Programming...