What this tool does
Search Inside Screenshots is a browser-based utility that combines Optical Character Recognition (OCR) with full-text search capabilities to let you find specific words and phrases within uploaded images. Unlike standard OCR tools that only extract text, this tool adds a searchable layer on top of the extraction results. You upload one or more screenshots, the tool processes each image using Tesseract.js to extract all visible text, and then you can type a search query to instantly locate and highlight matching text across every processed image. The entire workflow runs locally in your browser, meaning no images or extracted text are transmitted to external servers. This makes it suitable for working with sensitive content such as private messages, confidential documents, or proprietary interfaces. The tool supports common image formats including PNG, JPEG, WebP, and BMP, and can handle multiple images simultaneously with individual progress tracking and confidence scores for each result.
How it works
The tool uses Tesseract.js, an open-source OCR engine compiled to WebAssembly, running entirely within your web browser. When you upload an image, the following steps occur in sequence. First, the image is loaded into memory as a data URL without leaving the browser. Second, the Tesseract OCR engine analyzes the image by segmenting it into regions, identifying character boundaries, and matching each character against trained language models. During this phase, a progress indicator shows the percentage of the recognition pass that has been completed. Third, once text extraction finishes, the tool reports a confidence score between 0 and 100 percent that represents the OCR engine's assessment of how accurately it recognized the characters. Higher scores indicate clearer text and more reliable results. Fourth, the extracted text is displayed in a readable format alongside the original image thumbnail. At this point, you can enter a search query in the search box. The tool performs case-insensitive matching across all extracted text and highlights every occurrence of the search term using visual markers. A match counter displays the total number of occurrences found across all images, and each image card shows its individual match count. You can copy the extracted text from any single image or copy all results at once for further use.
Who should use this
This tool is useful for a range of practical scenarios. Quality assurance testers can upload screenshots of application interfaces to search for specific error messages, labels, or UI text without manually reading through each image. Customer support agents who receive screenshots from users can quickly extract and search for error codes or account identifiers embedded in the images. Researchers gathering data from charts, infographics, or scanned documents can extract and search through the text content to locate specific figures or terminology. Developers debugging mobile applications can capture screenshots of log outputs and search for particular log entries or stack trace fragments. Legal professionals reviewing document screenshots can search for specific clause language or key terms. Anyone who receives important information as images rather than text, such as screenshots of chat conversations, configuration settings, or receipts, can use this tool to make that information searchable and copyable.
Worked examples
Example 1: A software tester uploads three screenshots of a web application showing different error states. After OCR processing completes with confidence scores of 92 percent, 87 percent, and 78 percent respectively, the tester types "timeout" in the search box. The tool highlights two occurrences in the first image ("Connection timeout after 30s" and "Request timeout") and one occurrence in the third image ("Session timeout detected"), while the second image shows no matches. The total match count displays 3.
Example 2: A product manager receives five screenshots of competitor applications and wants to identify which ones mention "free trial" in their interfaces. After uploading all five images and allowing OCR to process them, the manager searches for "free trial" and finds matches highlighted in two of the five screenshots, making it straightforward to identify which competitors prominently display trial offers.
Example 3: An accountant receives a batch of receipt images and needs to find a specific transaction. After uploading eight receipt screenshots, the accountant searches for the vendor name "Staples" and the tool highlights the matching receipt, showing the full extracted text including the date, items purchased, and total amount. The accountant then copies the extracted text for their expense report.
Limitations
OCR accuracy depends heavily on image quality. Blurry, low-resolution, or heavily compressed images will produce lower confidence scores and may contain recognition errors. Text rendered in decorative or stylized fonts may not be recognized correctly, as the OCR engine is trained primarily on standard typefaces. Handwritten text recognition is limited and will generally produce unreliable results compared to printed or typed text. The tool currently supports English language recognition, and text in other languages or scripts may not be extracted accurately. Very large images may take longer to process, as all computation happens in the browser and is limited by the device's processing power. Images with complex backgrounds, overlapping text, or very small font sizes may produce partial or inaccurate extraction results. The search function performs literal string matching rather than fuzzy or semantic matching, so minor OCR errors in extracted text may cause searches to miss results that contain recognition mistakes.
FAQs
Q: Are my images uploaded to a server for processing? A: No. All OCR processing is performed locally in your browser using Tesseract.js compiled to WebAssembly. Your images never leave your device, which makes this tool safe for processing confidential or sensitive screenshots.
Q: What image formats are supported? A: The tool accepts common image formats including PNG, JPEG, WebP, BMP, and GIF. For the most accurate OCR results, use PNG or high-quality JPEG images with clear, readable text.
Q: Why is the confidence score low for my image? A: A low confidence score usually indicates that the OCR engine had difficulty recognizing text in the image. Common causes include low image resolution, blurry text, unusual fonts, text overlapping with background graphics, or very small font sizes. Try uploading a higher-resolution or clearer version of the image.
Q: Can I search across multiple images at once? A: Yes. After uploading and processing multiple images, any search query you enter will be matched against the extracted text from all images simultaneously. The tool shows the total match count and highlights matches individually within each image result.
Q: How long does OCR processing take? A: Processing time varies based on image size, text density, and your device's processing capability. A typical screenshot processes in 2 to 10 seconds. Larger images or those with dense text may take longer. Progress is shown in real time for each image being processed.
Q: Can I copy the extracted text? A: Yes. Each image result includes a copy button that places the extracted text onto your clipboard. When you have processed multiple images, a copy-all button lets you copy the combined text from every image at once.
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