Algorithms use for Image Recognition

Algorithms use for Image Recognition
Algorithms use for Image Recognition

Algorithms use for Image Recognition

In our previous article, I have given you a brief about the Image Recognition and its working. I had mentioned about few algorithms in that. Today we are going to discuss Algorithms use for Image Recognition.

Image Classifier: One type of Image Recognition Algorithm is an image classifier. It takes a part of the image or image as an input and predicts what the image contained.

Let’s take an example to create a classification algorithm that can identify the image with cats, you need to train a neural network with thousands of cat images and thousand of the image of background with the cat. The algorithm will learn the features to extract the features that identify a cat object and correctly classify images that contain a cat.

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While most Algorithms use for Image Recognition are classifiers, other algorithms can be used to perform more complex activities like Recurrent Neural Network can be used to give captions to the images.

Pattern matching and gradient matching: Pattern matching algorithm is a technique which enables localization of templates. Such a template pattern can be a specific facial feature, an object of known characteristics or a speech pattern such as a word. Deep Convolutional Neural Networks process the image by passing it through different hidden layers and at each layer produce a vector with classification information about the image. These vectors are extracted from the network and are used as the features of the image. 

Face Recognition: It is a Popular recognition algorithm include principal component analysis using eigenfaces, linear discriminant analysis, graph matching using the Fisherface algorithm, the hidden Markov model, the multilinear subspace learning using tensor representation, and the neuronal motivated dynamic link matching.

License plate matching: An improved Template Matching algorithm is proposed to recognize license plate characters. For recognition of number plate, a new algorithm is proposed, which uses dynamically generated license plate characters as database template and recognition is done using correlation technique.

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