Multi-dimensional Image Detection Using Color Bar Indicators

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Solution Overview

Problem

Current image detection systems for cameras and car machines face challenges in achieving high accuracy and efficiency due to incomplete detection data when only detecting either imaging content or color, leading to increased costs and insufficient detection accuracy, and lack of hardware-in-loop detection capabilities.

Innovation Solution

An image detection method and apparatus that performs multi-dimensional detection using a preset image detection network to extract feature data from acquired images, incorporating both imaging content and color bar indicators to enhance detection accuracy without the need for a specific detection environment, thereby enabling hardware-in-loop detection.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If only imaging content detection is performed, then detection cost is reduced, but detection accuracy is insufficient

Engineering Contradiction:

Improvedetection accuracyVSAvoiddetection system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The detection system is segmented into two independent detection modules: one for imaging content and another for color information. Each module processes specific features separately before merging results, allowing the system to achieve comprehensive detection accuracy without requiring a single complex monolithic system.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent extends detection from a one-dimensional approach (only imaging content) to a two-dimensional approach by adding color information as a second dimension. This dimensional expansion enables the system to capture both content and color characteristics, significantly improving detection accuracy without proportionally increasing system complexity.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

2Measurement precision

If only color detection is performed, then detection cost is reduced, but detection accuracy is insufficient

Engineering Contradiction:

Improvedetection accuracyVSAvoiddetection system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent extends detection from a one-dimensional approach (only color) to a two-dimensional approach by adding imaging content as a second dimension. This dimensional expansion enables the system to capture both color and content characteristics, significantly improving detection accuracy without proportionally increasing system complexity.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

3Measurement precision

If multi-dimensional detection is performed, then detection accuracy is improved, but detection cost increases

Engineering Contradiction:

Improvedetection accuracyVSAvoiddetection cost

Core Design Contradiction:

Measurement precisionVSQuantity of substance

Solution Approach 1:

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent extends detection from a one-dimensional approach to a two-dimensional approach by adding color information as a second dimension. This dimensional expansion enables the system to capture both content and color characteristics, significantly improving detection accuracy without proportionally increasing system complexity.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

4Reliability

If hardware-in-loop detection is implemented, then detection reliability is improved, but device complexity increases

Engineering Contradiction:

Improvedetection reliabilityVSAvoiddetection system complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The detection system performs self-verification through hardware-in-loop detection, where the acquired image is automatically checked against detection results. The system uses color bars as reference standards to self-evaluate imaging quality, eliminating the need for external verification equipment and reducing overall system complexity despite the added detection capabilities.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent utilizes color bars with specific color information as reference standards for self-verification. By detecting color bars in the acquired image and comparing their color characteristics against expected values, the system achieves reliable self-testing of imaging quality without requiring complex external measurement equipment.

Inventive Principle:

Principle #32Color changes

Data Source

PatentUS11798193B2Multi-dimensional image detection on at least two acquired images

Publication Date: 2023.10.24 BEIJING BAIDU NETCOM SCI & TECH CO LTD

AI summary

An image detection method and apparatus, an electronic device and a storage medium are provided, which relate to the fields of artificial intelligence, deep learning and image processing. The image detection method comprises: performing an acquisition processing on a to-be-detected imaging image to obtain an acquired image; extracting feature data of a target object in the acquired image through a preset image detection network in response to detection processing; performing a multi-dimensional detection comprising at least an imaging content indicator and a color bar indicator on the feature data of the target object according to the image detection network to obtain a detection result; wherein the target object includes imaging contents and color bars which are used to describe color information related to the imaging contents.