Correct latin alphabet formation assessment using neuron values

Structuring Elements of Hit or Miss to Identify Pattern of Benchmark Latin Alphabets Strokes

“…ANN is a computational model that replicate the capability of human brains neural networks to learn and relearn as its neural network changes based on input fed and output produced. It was applied in analyzing personality of a person based on offline handwritten small letter ‗t' [15][16] and to assess children handwriting based on the typology of stroke type, sequences, and direction of Latin alphabet formation [17][18]. The strokes are classified into three types of stroke patterns which are straight line, complex straight line and curve.…”

“…Each stroke would have its own range of BPNN neuron value. The tested handwriting values will then be compared to BPNN neuron value of reference alphabet [17]. In another research, BPNN values and correlation analysis methods were used to analyze the accuracy of six complex straight line Latin alphabet formations.…”