In intermediate-level image processing, the input provided to the algorithm is an image, and the output is the attributes of an image. Motion Analysis, Object labeling are examples of ...

Before you start looking for algorithms, you need to clearly define your problem and its scope. What is the goal of your image processing or computer vision project? What are the inputs and outputs?

One way to deal with changing lighting conditions is to adapt your image processing algorithms to different color spaces. Color spaces are mathematical models that represent the colors of an image ...

Sequential and parallel programming are good in their own paradigm. This paper analyses the performances of various basic image processing algorithms on GPU as well as CPU. Various images with a range ...

To extract 1024 pixel vital information, the related image processing algorithms include RGB to Gray conversion, Gamma encoding, Edge Detection and down sampling are described here. The comparative ...

Introduction Radio interferometry is a technique in radio astronomy where signals from two or more radio telescopes are ...

Artificial intelligence has the potential to improve the analysis of medical image data. For example, algorithms based ... to the decisions made in the post-processing of the predicted ...