Automatic Text Placement in Digital Images Using Saliency Masks

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Solution Overview

Problem

Conventional content editing systems require significant user effort to manually position and scale textual content within digital images, often resulting in suboptimal placement and cluttered compositions, especially when adding text to multiple images in workflows like collages or presentations.

Innovation Solution

The system automatically determines an optimal placement region for textual content within a digital image by identifying salient and non-salient portions using a saliency mask, prioritizing candidate regions based on size and proximity to the salient object, and adjusts the text to fit within this region, reducing manual input and improving visual balance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If text is positioned at a default position within the digital image, then the text placement process is simple and quick, but the text may obstruct salient objects and result in poor visual balance

Engineering Contradiction:

Improvetext placement simplicityVSAvoidtext placement accuracy

Core Design Contradiction:

Ease of operationVSManufacturing precision

Solution Approach 1:

The system automatically determines the optimal text placement region by analyzing the digital image itself to identify salient objects and calculate appropriate placement zones, eliminating the need for manual user intervention while achieving precise, aesthetically pleasing text positioning that avoids obstructing important image content

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system performs preliminary analysis of the digital image to identify salient objects and determine safe placement regions before text is actually added, ensuring that text placement decisions are made based on comprehensive image understanding rather than default positioning

Inventive Principle:

Principle #10Preliminary action

2Manufacturing precision

If user manually adjusts text size and placement, then text positioning accuracy can be improved, but user effort and time consumption increase significantly

Engineering Contradiction:

Improvetext positioning accuracyVSAvoiduser adjustment time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The system autonomously performs text positioning and sizing by automatically analyzing the image, identifying placement regions, and adjusting text parameters to fit within safe zones, completely eliminating the need for manual user adjustment while maintaining high positioning accuracy

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system replaces manual mechanical adjustment operations with automated computational image analysis and algorithmic text placement, substituting user interaction with intelligent software that calculates optimal text positioning based on image content understanding

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If text is added to multiple images in workflows like collages or presentations, then productivity can be maintained, but cumulative user effort and time investment become excessive

Engineering Contradiction:

Improvebatch processing capabilityVSAvoidcumulative user effort

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system processes each image independently by identifying salient objects and placement regions specific to each individual image, then applies text positioning automatically to multiple images in sequence, maintaining consistency across the batch while eliminating repetitive manual adjustments for each image

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system provides a universal automated text placement solution that works across multiple different images and workflow types (collages, presentations, etc.), handling diverse image content with a single integrated approach that eliminates the need for separate manual adjustment processes for each image type

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS11270485B2Automatic positioning of textual content within digital images

Publication Date: 2022.03.08 ADOBE INC

AI summary

Automatic positioning of textual content within digital images is leveraged in a digital medium environment. Initially, user input is received to add textual content to a digital image. A salient portion and a non-salient portion of the digital image are identified. The salient portion of the digital image contains a salient object which corresponds to the most important or noticeable object in a digital image, as opposed to non-salient objects which correspond to less important background objects or portions of an image. A placement region for the textual content within the non-salient portion of the digital image is automatically determined, and the digital image is modified by positioning the textual content within the automatically determined placement region of the digital image. Positioning the textual content may include automatically adjusting the textual content to fit within the placement region, such as by automatically scaling or aligning the textual content.