Paper Title:KNN classification of Kannada Characters using Hu’s Seven Variants and Zernike Moment Features


Identifying the text is one of the promising field of research in the domain of computer vision and pattern recognition. This paper copes with identity of kannada text. Eliminating noise and extracting the textual content from the scanned or captured picture is first step. Segmenting the lines and characters is the second step which is essential. Noise removal and extracting the textual content can be done by way of the usage of any noise filter and foreground subtraction algorithm. Otsu set of rules facilitates to gain the task of foreground extraction. Horizontal and Vertical Profiling is a method of extracting lines and words from the image document. Extracting the knowledge from the dataset the use of Hu’s Seven variations and Zernike Moments features helps to come over many problem. After training method knowledge is being generated through the usage of the above mentioned methods. KNN classifier is used to understand the unknown characters through the quest approach through calculating the capabilities.

Keywords:Computer Vision; Character Identificatoin; OCR Techniques;.