This system has a success rate of character segmentation of 100% and success rate on character recognition with genetic algorithm of 89,027% with one point crossover, 90,43% with two point crossover, 90,72% with uniform crossover. Linear Programming AlgorithmsOn this page Definition Large Scale Linear Programming Active-Set Medium-Scale linprog. Modul perkuliahan ini digunakan untuk mata kuliah algoritma dan pemrograman 1 pada jurusan teknik informatika yang terbagi menjadi 14 pertemuan dimulai dari pengenalan algoritma dan pemrograman sampai dengan mengimplementasikan algortima untuk membuat program sederhana.
To use the genetic algorithm method, given the process of resizing the template first so that the image size of the characters with the same template.
Genetic algorithm is used to find characters from the character image obtained by comparing the image with the chromosome of the train data. Preprocessing of input image consists of grayscale process, and thresholding. The designed system consists of five main processes: preprocessing the input image, vertical and horizontal line segmentation, line segmentation and character with automatic cropping, resizing template, and character recognition using genetic algorithm. Writing can be uppercase, lowercase, or numbers. Handwriting recognition system using genetic algorithm is an Optical Character Recognition system which receives input in the form of handwritten image in scanned box and produces output in the form of characters from the handwriting.
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