Cilj diplomske naloge je izdelava sistema za optično prepoznavanje znakov z uporabo
nevronske mreže. Računsko zahtevne dele sistema smo pohitrili z uporabo grafične
procesne enote (GPU). Naš sistem za OCR opišemo v treh glavnih sklopih: razbitje
dokumenta na znake (segmentacija), prepoznavanje posamičnih znakov ter
paralelizacija izvajanja na GPU. Zatem predstavimo aplikacijo, v katero smo
integrirali našo rešitev. Rezultati testiranj so pokazali, da je natančnost prepoznavanja
znakov OCR-A in OCR-B okrog 98%, Courier New pa 92%, medtem ko je pohitritev
izvajanja kode na GPU bila minimalno petkratna napram izvajanju na CPU.The goal of this diploma work is to develop a system for optical character recognition (OCR) by using neural network. Computationally intensive parts of the system are going to be implemented on the graphics processing unit (GPU). We present our OCR system in three main parts: segmentation of document on characters, recognition of individual characters, and parallelization of execution on the GPU. Afterwards, we present an application with integrated our solution. Results of testing pointed out that the accuracy of OCR-A and OCR-B characters recognition was around 98%, while at Courier New characters this rate was 92%. A code execution on GPU was at least five times faster than on CPU
