Knowledge in Braille is ultimately necessary to maintain learning for the visually impaired. In the Philippines, class attendance has been showing low rates for visually impaired students caused by the shortages of teachers and the absence of the specialized tools intended for teaching them. A proposed solution in addressing this problem is the usage of computers for the automation in the process of the extraction of information in Braille which can facilitate teaching. In recent years, a considerable amount of effort and attention have been devoted to the development of this kind of technology however in languages other than Filipino Braille. Codes in Filipino Braille with its contractions, and even the Filipino language itself has unique features as compared with other languages. In this paper, a system is proposed which uses machine vision in recognizing Filipino Braille codes including one-cell and two-cell contractions. Synthetic Braille images undergo cascade object detection, image processing, extraction of HOG features to develop the three-stage multiclass SVM classifier. Experimental evaluation results reveal a good performance of Filipino Braille classification and translation to texts.