Image Layer Mask Cropping for Precise Object Erasing
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Solution Overview
Problem
Existing image processing technologies lack an efficient method for precisely erasing unwanted parts of an image during creative retouching, leading to issues like information loss and edge blur due to imprecise area determination.
Innovation Solution
An image erasing method that involves obtaining an original image layer and an occluding image layer, identifying the target object, cropping a mask based on the occluding layer, and erasing the local area using the cropped mask, thereby determining the area to be erased with high precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If user manually defines area to be erased, then ease of operation is improved, but manufacturing precision deteriorates due to imprecise area determination
Solution Approach 1:
The system automatically identifies the target object and determines the erasure area using AI algorithms and mask processing, eliminating the need for manual user definition. The occluding image layer automatically provides the precise area boundaries through its transparent and opaque regions, allowing the system to self-determine the exact erasure zone without user intervention.
Solution Approach 2:
The patent introduces a mask as an intermediary element that bridges the gap between the original image and the occluding image. The mask is generated by cropping the first mask (from target object identification) based on the occluding image layer, creating a precise second mask that accurately defines the erasure area. This intermediary mask enables high-precision erasure by mediating between automatic object detection and the final erasure operation.
2Manufacturing precision
If automatic area determination is used, then manufacturing precision is improved, but loss of information increases due to potential inaccuracies
Solution Approach 1:
The patent applies partial action by using the occluding image layer's transparent and opaque regions to selectively erase only the necessary portions of the target object. The second mask is cropped to match exactly the area that needs erasure, avoiding excessive erasure of surrounding areas. This partial action approach maintains precision while minimizing information loss by erasing only what is strictly necessary.
Solution Approach 2:
The patent applies local quality by creating a localized erasure effect only in the specific area defined by the second mask. The erasure operation is confined to the precise boundaries determined by the cropped mask, ensuring that only the local area overlapping both the target object and the occluding image is affected. This localized approach preserves information in surrounding areas while achieving precise erasure where needed.
3Device complexity
If traditional erasure methods are used, then device complexity is reduced, but productivity deteriorates due to repeated adjustments
Solution Approach 1:
The patent applies preliminary action by pre-processing the target object identification and generating the mask before the actual erasure operation. The system identifies the target object, creates a first mask, crops it based on the occluding image layer to generate a second mask, and prepares the occluding image layer in advance. This preliminary preparation eliminates the need for repeated adjustments during erasure, as all parameters are predetermined, thereby significantly improving retouching efficiency.
Solution Approach 2:
The patent merges multiple operations into a unified automated process. The target object identification, mask generation, mask cropping, and erasure execution are combined into a single integrated workflow. The system simultaneously processes the original image layer, occluding image layer, and mask operations, eliminating the need for separate manual adjustment steps and thereby improving productivity without significantly increasing perceived device complexity.
Data Source
AI summary
The present disclosure relates to an image erasing method, an apparatus, an electronic device, and a storage medium. The method includes: obtaining an original image layer and an occluding image layer, wherein the original image layer includes a target object, and the occluding image layer occludes at least part of the target object; identifying the target object in the original image layer to obtain a first mask; cropping the first mask based on the occluding image layer to obtain a second mask; and erasing a local area of the occluding image layer based on the second mask.