Digital Image Processing

This course provides a comprehensive dive into digital image processing, blending theoretical knowledge with hands-on coding practice. It begins with the fundamentals of image formation through cameras and the representation of digital images. Participants will engage in manipulating images using basic mathematical operations such as addition, multiplication, negative, gamma correction, and piecewise transformations.

Through these exercises, they will develop a deep understanding of how these operations alter images at the pixel level, with histograms serving as a tool to visualize the impact. As participants work through these tasks, they will come to realize that image processing is fundamentally about performing mathematical operations on matrices, gaining an intuitive sense of what happens to an image when these basic operations are applied.

Upon completion, participants will be able to:

• Understand the fundamentals of digital image processing, image acquisition, and digitization

• Apply gray value/intensity transformations (addition, multiplication, negative, gamma, piecewise linear) to enhance images

• Use histograms to visualize the impact of image processing operations, including histogram equalization

• Apply noise reduction and smoothing techniques such as local averaging, Gaussian smoothing, and median filtering

• Perform image segmentation using thresholding techniques, including Otsu's method and adaptive thresholding

• Apply edge detection techniques based on Prewitt, Sobel, and Robert operators

Duration

2-day program

Methodology

Physical face-to-face, dynamic education and development.

Target Audience

Suitable for individuals new to digital image processing, including sales engineers, software engineers, technical support engineers, and manufacturing engineers.

Course Level

Beginner — an introductory course for individuals new to digital image processing.

Pre-requisites

No formal prerequisites; basic computer literacy and an interest in coding/image processing is recommended.