In the previous chapter, our main focus was filtering an image and applying different transformations on it. These are good techniques to analyze images but are not sufficient for the majority of computer vision tasks. For example, if we were to make a product detector for a shopping store, computing only edges may not be enough to say whether the image is of an orange or an apple. On the other hand, if a person is given the same task, it is very intuitive to differentiate between an orange and an apple. This is because of the fact that human perception combines several features, such as texture, color, surface, shape, reflections, and so on, to distinguish between one object with another. This motivates to look for more details that relates to complex features of objects. These complex features can then be used in high level image vision tasks like image recognition...
Germany
Slovakia
Canada
Brazil
Singapore
Hungary
Philippines
Mexico
Thailand
Ukraine
Luxembourg
Estonia
Lithuania
Norway
Chile
United States
Great Britain
India
Spain
South Korea
Ecuador
Colombia
Taiwan
Switzerland
Indonesia
Cyprus
Denmark
Finland
Poland
Malta
Czechia
New Zealand
Austria
Turkey
France
Sweden
Italy
Egypt
Belgium
Portugal
Slovenia
Ireland
Romania
Greece
Argentina
Malaysia
South Africa
Netherlands
Bulgaria
Latvia
Australia
Japan
Russia