- Support Vector MachinesThese machines make
histograms of images that contain the target objects and also of images that do not contain them. The algorithms will
compare the parameters of various parts of the image to check for matches.
- Bag of features modelsThese models take the image to be scanned and a sample photo of the object to be found to match the features of the sample photo to various parts of the target image to see if any matches are found.
- Viola-Jones algorithmPerhaps one of the best known, Viola-Jones is a
facial recognition algorithm widely used in the days before convolutional neural networks, as it
scans faces and extracts features that were compared in a series of classifiers.
To successfully find a match, a test image must generate a positive result from each of these classifiers.
- Image recognition models with Deep LearningDeep learning has fueled the development of image recognition programs such as
YOLO, SSD, and RCNN, which use convolution layers to analyze an image or photograph