Recognize Text in Images Using OCR

Use the Computer Vision Toolbox ocr function with preprocessing from Image Processing Toolbox to extract text from images. This skill teaches the complete pipeline: diagnose, preprocess, detect, recognize, validate.

When to Use

• Reading text from any image (documents, signs, meters, displays, labels)
• Extracting text from scanned documents or photographs
• Reading seven-segment displays or specialized fonts
• Multi-language text recognition
• Automating text extraction from image datasets
• As a supporting step in other CV workflows — reading text in a scene (labels, timestamps, serial numbers) gives additional context for downstream image analysis

When NOT to Use

• Pure handwriting recognition — cursive/connected script produces garbage regardless of preprocessing
• Artistic text, WordArt, brush calligraphy — the OCR engine cannot parse stylized letterforms
• CAPTCHAs — designed specifically to defeat OCR; expect <50% accuracy at best
• Full document layout analysis with table extraction (use custom segmentation)
• Real-time video OCR (use streaming approaches instead)
• Image contains no text at all