(untitled) (International Journal of Engineering and Computer Science, 2015)
Detecting text in natural images is an important prerequisite. Text Characters and Strings provide valuable information for many applications, extracting text directly from natural scene images or videos is a challenging task because of diverse text patterns and various background interferences. In this paper an attempt is made to extract text in Natural Scene image. This text detection algorithm employs edge-Enhanced Maximally Stable Extremal Regions as basic letter candidates. These candidates are then filtered using geometric and stroke width information to exclude non-text objects. Letters are paired to identify text lines, which are subsequently separated into words. The coding has implemented in MATLAB R2014a and the qualitative analysis is done. Based on the simplicity of eliminating cluttered background. we followed other techniques in extracting text easily such as color thresholding app and Region of interest (ROI).According to the statements in text extracted from natural images the controlling of electrical motors can also be done. This can be explained by hardware implementation of text extraction application using ARDUINO kit.