ABSTRACT
Image-processing techniques have a significant role from image acquisition, preprocessing, and segmentation to image analysis. This chapter provides a systematic study on the importance of image processing with its application in the domain of computer vision. It also gives a clear conceptual information about images’ file formats and their types used for image processing. In the image processing process, the image is first acquired, and multiple image preprocessing techniques are used, such as resizing, noise removal, filtering, and contrast enhancement. Then, several image segmentation techniques are applied over this image, such as edge detection, thresholding, region growing, and clustering to get an output of enhanced high-quality image to perform further analysis. Image analysis is a key step to the image processing which uses segmentation, feature extraction, and classification for effective analysis and to extract important information from the image. Our study not only provides a substantial introduction to image-processing techniques but also presents the importance of image processing in machine learning and deep learning domain. Machine learning has taken image processing to an advanced level since the detection of objects within the image is now achievable because of 118many machine learning algorithms. Deep learning uses multilayer neural networks like CNN or RCNN that can help in extracting important specific information from input images.
