Image Editor Censor

Purpose: The tool provides censorship capabilities for images used in media, publishing, or social platforms. It supports three censoring methods (blur, pixelation, and solid blackout) and can redact faces, license plates, logos, or other sensitive regions. Users can apply edits to a single image or to batches, preserving image resolution and color profile when possible.
Aimed at professionals who must comply with privacy rules or platform policies, the tool emphasizes reliable redaction and audit-friendly outputs.
Core logic: The system accepts an image and a set of redaction rules, then applies the selected method to specified regions. It supports mandatory inputs (image, method) and optional features (batch mode, intensity controls, and multiple formats). Outputs are generated with preserved dimensions by default and can include metadata for traceability.
Algorithms: Blur uses a Gaussian-like kernel; Pixelate performs block averaging within regions; Blackout fills regions with a solid color. If auto-detection is enabled, a lightweight detector searches for faces and license plates; manual regions can override or supplement detections.
Who benefits: editors, journalists, moderators, and compliance teams needing consistent redaction across assets while maintaining image integrity. Unique value: focus on censorship fidelity, batch processing, and non-destructive workflows that minimize rework. Core features include region specification (manual or auto), method options, intensity controls, and export flexibility.
Use cases: redacting faces in news photos, masking license plates in traffic footage, or obscuring logos in sponsored content.