This paper proposes a recognition model for English
handwritten (lowercase, uppercase and letter) character
recognition that uses Freeman chain code (FCC) as the
representation technique of an image character. Chain code
representation gives the boundary of a character image in which
the codes represent the direction of where is the location of the
next pixel. An FCC method that uses 8-neighbourhood that starts
from direction labelled as 1 to 8 is used. Randomized algorithm is
used to generate the FCC. After that, features vector is built. The
criteria of features to input the classification is the chain code
that converted to 64 features. Support vector machine (SVM) is
chosen for the classification step. NIST Databases are used as
the data in the experiment. Our test results show that by applying
the proposed model, we reached a relatively high accuracy for
the problem of English handwritten recognition.