5 EASY Ways To Integrate Image Processing In Your Apps
What does image processing mean? According to Gonzalez and Rafael in 2018, Image Processing or Digital Image Processing refers to processing digital images using a digital computer. Note that a digital image is composed of a finite number of elements, each element has a particular location and value. These elements are called picture elements, image elements, pels, and pixels. Pixel is the term used most widely to denote the elements of a digital image. Since images are defined over two dimensions (perhaps more), digital image processing may be modeled in the form of multidimensional systems. How is digital image processing better? As a subcategory or field of digital signal processing, digital image processing has many advantages over analog image processing. It allows a much wider range of algorithms to be applied to the input data and can avoid problems such as the build-up of noise and distortion during processing. The generation and development of digital image processing are mainly affected by three factors: First, the development of computers; second, the development of mathematics (especially the creation and improvement of discrete mathematics theory); third, the increasing demand for a wide range of applications in environment, agriculture, military, industry, medical science, etc. Image Processing is frequently used in ‘Computer Vision’. Don’t be confused-we are going to talk about the difference between these terms and how they connect. Image Processing vs Computer Vision The main difference between Image Processing and Computer Vision approaches is the goals (not the methods used). For example, if the goal is to enhance an image for later use, then this may be called image processing. If the goal is to emulate human vision, like object recognition, event detection, or automatic driving, then it may be called computer vision. Both Image Processing algorithms and Computer Vision (CV) algorithms take an image as input; however, in image processing, the output is also an image, whereas in computer vision the output can be some features/information about the image. Read our previous article about Computer Vision here: Why use Python for Image Processing? Now, almost every image processing or computer vision library has a form of scripting interface in its main functions. Most of the time, this scripting language is Python (this article shows the power of Delphi to provide a nice GUI for Python scripting power). Developers favor this particular ecosystem because of the following: Easy to learn and easy to use, without losing the quality of programming decisions. Python has been on the market for a long time and has been established. Python continues to evolve dynamically. With Python, you can use the coolest OOP solutions and you can write simple and effective code. Python provides a huge number of libraries that solve the whole range of programming problems. How to use Pillow, Matplotlib, scikit-learn, scikit-image, and Mahotas Python libraries to perform Image Processing tasks All of them would be integrated with Python4Delphi to create Windows Apps with Image Processing capabilities. Prerequisites Before we begin to work, download and install the latest Python for your platform. Follow the Python4Delphi installation instructions mentioned here. Alternatively, you can check out the easy instructions found in the Getting Started With Python4Delphi video by Jim McKeeth. Time to get Started! First, open and run our Python GUI using project Demo1 from Python4Delphi with RAD […]
