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arXiv · 2104.08052

ScreenSeg: On-Device Screenshot Layout Analysis

Manoj Goyal·Rachit S Munjal·Sukumar Moharana·Deepak Garg·Debi Prasanna Mohanty·Siva Prasad Thota
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Abstract

We propose a novel end-to-end solution that performs a Hierarchical Layout Analysis of screenshots and document images on resource constrained devices like mobilephones. Our approach segments entities like Grid, Image, Text and Icon blocks occurring in a screenshot. We provide an option for smart editing by auto highlighting these entities for saving or sharing. Further this multi-level layout analysis of screenshots has many use cases including content extraction, keyword-based image search, style transfer, etc. We have addressed the limitations of known baseline approaches, supported a wide variety of semantically complex screenshots, and developed an approach which is highly optimized for on-device deployment. In addition, we present a novel weighted NMS technique for filtering object proposals. We achieve an average precision of about 0.95 with a latency of around 200ms on Samsung Galaxy S10 Device for a screenshot of 1080p resolution. The solution pipeline is already commercialized in Samsung Device applications i.e. Samsung Capture, Smart Crop, My Filter in Camera Application, Bixby Touch.

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Manoj Goyal, Rachit S Munjal, Sukumar Moharana, Deepak Garg, Debi Prasanna Mohanty, Siva Prasad Thota. 2021-04-16. ScreenSeg: On-Device Screenshot Layout Analysis. https://arxiv.org/abs/2104.08052

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