Bộ sách luyện thi ETS 2023 LC&RC
199,000₫
299,000₫
Sách keo gáy, Bìa mềm
Thể loại:Computers - Hardware
Năm:2019
In lần thứ:1
Ngôn ngữ:english
Trang:274 / 279
Utilize modern methods for digital image processing and take advantage
of the many time-saving templates provided for all of the projects in
this book.
Modern Algorithms for Image Processing approaches the
topic of image processing through teaching by example. Throughout the
book, you will create projects that resolve typical problems that you
might encounter in the world of digital image processing. Some projects
teach you methods for addressing the quality of images, such as reducing
random errors or noise and suppressing pulse noise (salt and pepper), a
method valuable for improving the quality of historical images. Other
methods detail how to correct inhomogeneous illumination, not by means
of subtracting the mean illumination, but through division, a far more
efficient method. Additional projects cover contrasting, and a process
for edge detection, more efficient than Canny's, for detecting edges in
color images directly, without converting them into black and white
images.
What You'll Learn
• Apply innovative methods for suppressing pulse noise, enhancing contrast, and edge detection
• Know the pros and cons of enlisting a particular method
• Use new approaches for image compression and recognizing circles in photos
•
Utilize a valuable method for straightening photos of paintings taken
at an oblique angle, a critical concept to understand when using flash
at a right angle
• Understand the problem statement of polygonal approximation of boundaries or edges and its solution
• Use a new method for detecting bicycles in traffic
• Access complete source code examples in C# for all of the projects
Who This Book Is For
C#
developers who work with digital image processing or are interested in
informatics. The reader should have programming experience and access to
an integrated development environment (IDE), ideally .NET.
This book
does not prove or disprove theorems, but suggests methods for learning
valuable concepts that will enable you to customize your own image
processing projects.
