Abstract
In image processing, the radical scheme is required to propose a model for extracting the required content from an image. It plays a critical position to offer significant facts and needs methods in various automation arenas. By keeping the way of a parting textual content from images has proposed via following the sparse matrix illustration, grouping text components are based on heuristic rules and clustered into sentence generation. This paper directs a study on image analysis that inspects visual items as objects and different text patterns. Logistic Regression, Linear Discriminant Analysis naïve Bayes Algorithm are used to predict the image forms. This proposed work promotes the learning algorithm called Learning Vector Quantization Prediction Algorithm (LVQ Predict) is used to analysis the parts of the image. The features are extracted and classifies into printed and non-printed texts. Further, these texts are normalized and documented.
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