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Publisher : CreateSpace Independent Publishing Platform (December 26, 2016)
Language : English
Paperback : 232 pages
ISBN-10 : 1541286022
ISBN-13 : 978-1541286023
Item Weight : 1.68 pounds
Dimensions : 8.5 x 0.55 x 11 inches
Image processing and computer vision are important fields in the realm of artificial intelligence and machine learning. MATLAB, a powerful software tool, provides a comprehensive platform for implementing various image processing and computer vision algorithms.
In this post, we will discuss a practical approach for image processing and computer vision in MATLAB. We will cover the basic steps involved in processing and analyzing images using MATLAB, along with some common techniques and algorithms.
1. Loading and displaying images:
The first step in image processing is to load an image into MATLAB using the ‘imread’ function. Once the image is loaded, it can be displayed using the ‘imshow’ function.
2. Preprocessing images:
Image preprocessing involves enhancing the quality of the image before further analysis. This can include operations such as noise reduction, image sharpening, and contrast enhancement. MATLAB provides various functions for performing these operations, such as ‘imfilter’ for filtering and ‘imadjust’ for adjusting image contrast.
3. Image segmentation:
Image segmentation is the process of dividing an image into different regions or objects. MATLAB offers several segmentation algorithms, such as thresholding, edge detection, and clustering. These algorithms can be used to identify and extract specific features or objects in an image.
4. Feature extraction:
Once the image has been segmented, features can be extracted from the regions of interest. These features can include color, texture, shape, and size. MATLAB provides functions for extracting features, such as ‘regionprops’ for computing region properties and ‘extractFeatures’ for extracting features from images.
5. Object detection and recognition:
Object detection and recognition are key tasks in computer vision. MATLAB provides tools for implementing object detection algorithms, such as Haar cascades and deep learning models. These algorithms can be used to detect and recognize objects in images or videos.
6. Image classification:
Image classification is the process of categorizing images into different classes or categories. MATLAB offers several classification algorithms, such as support vector machines, k-nearest neighbors, and deep learning models. These algorithms can be trained on a labeled dataset to classify images into different classes.
In conclusion, MATLAB provides a comprehensive platform for image processing and computer vision. By following a practical approach and utilizing the various tools and algorithms available in MATLAB, you can implement sophisticated image processing and computer vision applications. Whether you are a beginner or an expert in the field, MATLAB offers a versatile and powerful environment for exploring and implementing image processing and computer vision algorithms.
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