Abstract The aim of this paper is to propose a novel techniq ue for Arabic/Farsi handwritten digit recognition. We constructed an invariant and efficient feature set by combination of four directional Chain Code Histo gram (CCH) and Histogram of Oriented Gradient (HOG). To achieve hi gher recognition rate, we extracted local features at two levels with grids 2×2, 1×1 and it causes a partial overlapping of zones. Our proposed feature set has 164 dimensio ns. For classification phase, Support Vector Machine (SVM) with radial bas is function kernel was used. The system was evaluated on HODA handwritten digit dataset which consist of 60000 an d 20000 training and test samples, respectively. The experimental results represent 99.31% classification rate. Further, 59fo ld cross validation was applied on whole 80000 samp les and 99.58% accuracy was obtained.

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