Image Processing Applications on Raspberry Pi is a beginner course on the newly launched Raspberry Pi 3 and is fully compatible with Raspberry Pi 2 and Raspberry Pi Zero.
The course is ideal for those who are new to the Raspberry Pi and want to explore more about it.
You will learn the components of Raspberry
Pi, connecting components to Raspberry Pi, installation of NOOBS
operating system, basic Linux commands, Python programming and building
Image Processing applications on Raspberry Pi.
This course will take beginners without any coding skills to a level where they can write their own programs.
Basics of Python programming language are well covered in the course.
Building Image Processing applications are taught in the simplest manner which is easy to understand.
Users can quickly learn hardware assembly and coding in Python
programming for building Image Processing applications.
By the end of this course, users will have enough knowledge about
Raspberry Pi, its components, basic Python programming, and execution of
Image Processing applications in the real time scenario.
The course is taught by an expert team of Electronics and Computer Science engineers, having PhD and Postdoctoral research experience in Image Processing.
Anyone can take this course. No engineering knowledge is expected. Tutor has explained all required engineering concepts in the simplest manner.
The course will enable you to independently build Image Processing applications using Raspberry Pi.
This course is the easiest way to learn and become familiar with the Raspberry Pi platform.
By the end of this course, users will build Image Processing applications which includes scaling and flipping images, varying brightness of images, perform bit-wise operations on images, blurring and sharpening images, thresholding, erosion and dilation, edge detection, image segmentation . User will also be able to build real-world Image Processing applications which includes real-time human face eyes nose detection, detecting cars in video, real-time object detection, human face recognition and many more.
The course provides complete code for all Image Processing applications which are compatible on Raspberry Pi 3/2/Zero.
My name is Steven Lawrence Fernandes and I am super-delighted that you are reading this!
I have a PhD in Machine Learning and Computer Vision and Postdoctoral research experience at University of Alabama Birmingham, USA. I have Bachelor’s and Master’s degree in Electronics and Communication Engineering. I have 5 years of experience in developing Computer Vision applications in Raspberry Pi. I am absolutely passionate about developing various innovative Computer Vision applications on Raspberry Pi and I am looking forward to sharing my passion and knowledge with you!