Adaptive Image Thresholding
Adaptive thresholding can segment an image by setting all pixels whose intensity values are above a threshold to a foreground value and all the remaining pixels to a background value.
The basic idea of adaptive thresholding is to use different threshold values for different regions of the image, rather than using a global threshold value for the en.
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Eigenfaces
Eigenfaces is a computer vision algorithm that was developed in the early 1990s by researchers at MIT to recognize faces in images.
The algorithm is based on the concept of eigenvectors.
The algorithm first performs Principle Component Analysis (PCA) on a large set of face images, which are then used as a set of “eigenfaces”.
The basic idea is that.
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Graph Cut Optimization
Graph cut algorithms are most commonly used in image segmentation to separate an image into multiple regions or segments based on color or texture.
First, a network flow graph is built based on the input image.
The graph cut algorithm is a method for partitioning a graph into two or more sets of vertices (also called nodes).
The goal is to minimize.
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Histogram of Oriented Gradients
The histogram of oriented gradients (HOG) is a feature descriptor used in computer vision for object detection.
It is used to represent the shape of an object by encoding the distribution of intensity gradients or edge directions within an image.
The basic idea behind HOG is to divide an image into small connected regions called cells, typically 8×.
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Resnet
ResNet (short for Residual Network) is a deep convolutional neural network architecture that was developed by researchers at Microsoft in 2015.
It is known for its performance on image classification and object detection tasks.
The key innovation in ResNet is the use of “residual connections” between layers.
This enables the network to better handl.
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Sift
The Scale-Invariant Feature Transform (SIFT) algorithm is a computer vision algorithm used for identifying and matching local features, such as corners or blobs, in images.
It was first described in a paper by David Lowe in 1999.
The SIFT algorithm is invariant to image scale and rotation.
SIFT is widely used in image matching, object recognition, .
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Surf
The Speeded Up Robust Features (SURF) algorithm is a feature detection and description method for images.
It is a robust and fast algorithm that is often used in computer vision applications, such as object recognition and image registration.
SURF is considered to be a “speeded up” version of the Scale-Invariant Feature Transform (SIFT) algorithm. .
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Viola-Jones
Viola-Jones is a computer vision algorithm for object detection, specifically for detecting faces in images.
It was developed by Paul Viola and Michael Jones in 2001.
The algorithm uses a technique called “integral image” that allows for fast computation of Haar features, which are used to match features of typical human faces.
The algorithm also u.
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Yolo
YOLO (You Only Look Once) is a computer vision algorithm used for object detection in images and videos.
It can process images and make predictions about the objects within them in a single pass, rather than requiring multiple passes through the image, as is the case with other object detection algorithms.
YOLO uses a convolutional neural network (.
