@article{MAKHILLIJSC201813221445,
    title = {Trace Transform Based Features for Offline Handwritten Jawi Word Recognition},
    journal = {International Journal of Soft Computing},
    volume = {13},
    number = {2},
    pages = {51-60},
    year = {2018},
    issn = {1816-9503},
    doi = {ijscomp.2018.51.60},
    url = {https://makhillpublications.co/view-article.php?issn=1816-9503&doi=ijscomp.2018.51.60},
    author = {Mohammad,Mohamad,Choong-Yeun,Khairuddin and},
    keywords = {Jawi,offline handwritten word recognition,Trace transform,feature extraction,signature,offline},
    abstract = {This study discusses offline handwritten Jawi recognition using the trace transform. We use two
attainable kinds of features from the trace transform which are the "object signature" and "triple feature". They
are invariant to affine distortion, generated by the trace transform to discriminate between offline handwritten
Jawi sub words. In trace transform, features construction of an image consists of tracing an image with straight
lines, along which certain functional of the image function are calculated in all possible orientations. An object
signature or a function of the orientation of the parallel lines is produced when a second functional is applied
over all values computed along parallel lines. The computed object signature is in a form of string of numbers.
A single number, triple feature is produced when a third functional over the string of numbers is applied. If the
functional used have some predefined properties, the feature can be used to characterise the handwriting
in an affine way. In this study, we also demonstrate the way of determining useful signatures and selecting
cross-correlation methods for the signature classification. The results of the recognition experiments
show that the object signature is a better feature than the triple feature in recognition of offline Jawi
words.}
    }