초록

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Abstract ▼ AI-Helper

Scene text extraction is crucial for diverse image-based applications due to the fact that the text provides contextual clues. Maximally stable extremal regions (MSER) are one of the most outstanding region detectors, and often used to detect text candidates in the preprocessing step of scene text e...

Scene text extraction is crucial for diverse image-based applications due to the fact that the text provides contextual clues. Maximally stable extremal regions (MSER) are one of the most outstanding region detectors, and often used to detect text candidates in the preprocessing step of scene text extraction. Once MSER is extracted, stroke information is needed to classify each candidate regions as text or background. The conventional stroke width transform (SWT) converts an intensity image into stroke width image based on edge points, and then extracts stroke information. This method is helpful to extract stroke information, but inappropriate for MSER to apply directly due to the fact that works based on edge points. In this paper, we propose a new method to make stroke width image for MSER. Especially, the proposed method can extract useful feature to classify a region into text or nontext about a degree that region is composed of parallel boundary besides stroke width information.

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