The Importance Of Image Classification

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Image classification is an area in image processing where the primary goal is to separate a set of images according to their visual content into one of a number of predefined categories. It is the problem of finding a map from images to a set of classes, not necessarily object categories. Each class is represented by a set of features (feature vector) and the algorithm that maps these feature vectors to a class uses machine learning techniques. The ability to perform multi-class image classification is an automatic task using computers is increasingly becoming important. This is due to the huge volume of image data is available, which are proving to be difficult for manual analysis. The difficulty arises due to lack of human experts, time complexity and poor quality images. The current market need to have techniques which can classify the images with minimum intervention from the users in an efficient and effective manner. The classification of unnatural plant leaves is a crucial process in botany and other industries. Moreover, the morphological features of leaves are used for plant classification or in early diagnosis of certain plant diseases (Chaudhary et al 2012). This Chapter describes a new approach referred as Hybrid Feature Extraction (HFE). It has three…show more content…
The selection of proper classifier is also very difficult for particular applications. Assigning images to pre-defined categories by analyzing the contents is defined as ‘Image classification or ‘Image categorization’. The process of image classification allows users to find the desired information faster by searching only the relevant categories and not the whole information space. Image classification normally involves the processing is of two main tasks:- (i) Feature extraction task – Extracts image features and forms a feature vector and (ii) Classification task – Uses the extracted features to discriminate the

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