1. A method, comprising: identifying a first region of an image; identifying a second region of the image; extracting contextual features from the first region of the image, the contextual features comprising at least one of gradient or intensity patterns; aggregating the contextual features; quantizing the aggregated extracted features as quantized contextual features of the first region; determining, using a first classifier, that the quantized contextual features are consistent with image data comprising a glyph; determining that the first region contains a glyph; determining that the second region does not contain a glyph; stopping further processing of the second region; identifying a candidate glyph corresponding to a maximally stable extremal region (MSER) in the first region of the image; determining a plurality of glyph feature descriptors based on the candidate glyph, including one or more of determining the candidate glyph's aspect ratio, compactness, solidity, stroke-width to width, stroke-width to height, convexity, raw compactness, or a number of holes included in the candidate glyph; determining that the candidate glyph comprises a first glyph, using the determined glyph feature descriptors, the quantized contextual features, and a first model; and performing optical character recognition (OCR) on the first glyph.