Remote Working Machine Imaging With Grayscale-to-Color Restoration
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Solution Overview
Problem
Existing control systems for working machines face challenges in accurately determining situations during autonomous driving, particularly at intersections, due to delays in image transmission, which can be mitigated by reducing data capacity through techniques like reducing image resolution in regions of interest.
Innovation Solution
A control system that converts color images to grayscale images and transmits these to a remote system, using a learning model to restore color images, while also incorporating a relearning mechanism to adapt to changes in the environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If color images are transmitted to reduce data capacity, then transmission delay is reduced, but image data size cannot be sufficiently reduced
Solution Approach 1:
The invention extracts only the essential luminance information from color images by converting them to grayscale images before transmission. This extraction process removes redundant color data while preserving the critical brightness information needed for operator decision-making, thereby significantly reducing transmission data volume and delay.
Solution Approach 2:
The invention changes the parameter representation of image data by converting from color space (RGB with 3 channels) to grayscale space (single luminance channel). This parameter transformation reduces the data dimensionality while maintaining the essential visual information, achieving efficient compression without requiring complex compression algorithms.
2Loss of time
If grayscale images are transmitted instead of color images, then transmission delay is reduced, but color information is lost
Solution Approach 1:
The invention introduces a learning model as an intermediary that predicts and restores color information from grayscale images. This mediator receives the compressed grayscale data, uses learned relationships between luminance and color to reconstruct the color information, and outputs restored color images to the operator, thereby preserving color perception while maintaining transmission efficiency.
Solution Approach 2:
The invention performs preliminary color-to-grayscale conversion at the transmission end before data sends, and preliminary color restoration at the reception end using the learning model. This preliminary processing approach ensures that color information is not completely lost but is efficiently compressed for transmission and then restored, reducing overall transmission delay.
3Productivity
If image resolution is reduced to decrease data capacity, then transmission speed is improved, but image quality deteriorates
Solution Approach 1:
The invention applies different quality levels to different parts of the image processing pipeline: grayscale conversion maintains full spatial resolution for luminance information while reducing color dimensionality, and the learning model selectively restores color information in regions where it is most needed. This local quality approach preserves critical details while achieving efficient compression.
Data Source
AI summary
To provide a control system of a working machine and a control method of the working machine that enables an operator side to control the working machine, on the basis of an image transmitted from the working machine side.In a control system of a working machine which operates the working machine by an image from the working machine side, the working machine includes an image processing unit which converts a color image into a grayscale image; and a working machine communication unit which transmits the grayscale image from the working machine side to the system side, and the system includes a system communication unit which receives the grayscale image transmitted by the working machine; and a processing unit which restores a color image from the grayscale image, by the use of a learning model created using an original image of a working area, and an image in which tonal information is reduced from the original image.