diff --git a/sections/Chapter-1-sections/General-Introduction.tex b/sections/Chapter-1-sections/General-Introduction.tex index c7216f6d3809468f39e7732f9ef8324c6319a131..6d9772397428d176a1a82bb8ba5b51138f9a7137 100644 --- a/sections/Chapter-1-sections/General-Introduction.tex +++ b/sections/Chapter-1-sections/General-Introduction.tex @@ -6,7 +6,7 @@ The significance of digital image processing in industrial applications cannot b The evolution of digital image processing has been marked by several key developments. Initially, the field was limited by the computational resources available, with early applications focusing on basic image enhancement and restoration. However, the advent of powerful processors and the development of sophisticated algorithms have expanded the scope of image processing to include complex tasks such as pattern recognition, 3D reconstruction, and real-time image analysis. The integration of artificial intelligence and machine learning has further propelled the field, allowing for the development of intelligent systems capable of learning from data and improving over time. -For industries like Dassault Systems, which operates at the forefront of aerospace, defense, and industrial engineering, a comparative study of image processing libraries is crucial. These libraries, which provide pre-built functions and tools for image analysis, vary significantly in terms of performance, ease of use, and functionality. Selecting the right library can have a profound impact on the efficiency and effectiveness of image processing tasks. For instance, libraries such as OpenCV, TensorFlow, and MATLAB offer different strengths and weaknesses, and understanding these differences is essential for optimizing industrial applications. +For industries like Dassault Systems, which operates at the forefront of aerospace, defense, and industrial engineering, a comparative study of image processing libraries is crucial. These libraries, which provide pre-built functions and tools for image analysis, vary significantly in terms of performance, ease of use, and functionality. Selecting the right library can have a profound impact on the efficiency and effectiveness of image processing tasks. For instance, libraries such as OpenCV, Imagemagick and ImageSharp offer different strengths and weaknesses, and understanding these differences is essential for optimizing industrial applications. A comparative study of these libraries not only aids in selecting the most suitable tools for specific tasks but also highlights areas for potential improvement and innovation. By analyzing the performance of different libraries in various scenarios, industries can identify gaps in current technologies and drive the development of new solutions that better meet their needs. Moreover, such studies contribute to the broader field of digital image processing by providing insights into best practices and emerging trends.