Dynamic Plant Identification via Active Region Extraction
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Solution Overview
Problem
Conventional farming systems face inefficiencies in treating individual plants within a field, as they often apply treatments to entire areas, leading to waste and labor-intensive manual processes, with existing imaging technologies struggling to accurately identify and differentiate between crops and weeds.
Innovation Solution
A farming machine equipped with a plurality of image sensors tilted downwards to capture images of plants, using a control system to generate tiled images by discarding irrelevant data, identify active regions, and actuate treatment mechanisms, allowing for precise targeting and treatment of individual plants while reducing computational power and improving processing speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If overlapping fields of view are used to prevent gaps in plant detection, then detection accuracy is improved, but redundant image data increases processing complexity
Solution Approach 1:
The patent extracts only the relevant portion of the image (active region) for processing by discarding pixels outside the active region. This reduces redundant data from overlapping fields of view while maintaining complete plant detection coverage, resolving the contradiction between detection accuracy and processing complexity
Solution Approach 2:
The patent segments the image into active region pixels and non-active region pixels, processing only the active region segments that contain relevant plant information. This segmentation approach maintains detection accuracy while reducing overall processing complexity by excluding redundant overlapping areas
2Measurement precision
If high resolution imaging is used to identify individual plants, then detection precision is improved, but computational power requirements increase
Solution Approach 1:
The patent extracts only the active region containing individual plants for detailed processing, discarding the rest of the high-resolution image data. This maintains plant identification precision while significantly reducing computational power requirements by processing only necessary image portions
3Productivity
If the farming machine moves quickly through the field, then productivity is improved, but time for plant identification and treatment decreases
Solution Approach 1:
The patent extracts and processes only the active region pixels containing plant information, discarding irrelevant image data. This reduces identification time significantly, allowing the farming machine to maintain high productivity while having sufficient time to identify and treat individual plants
Solution Approach 2:
The patent applies partial action by processing only the necessary active region portion of the image rather than the entire image. This partial processing approach reduces identification time while maintaining adequate accuracy for individual plant treatment at high speeds
4Area of stationary object
If conventional spray treatment is applied to entire zones, then treatment coverage is improved, but treatment efficiency deteriorates due to waste
Solution Approach 1:
The patent applies treatment locally to individual plants based on their identification in the active region, rather than uniformly treating entire zones. This local quality approach eliminates waste by applying treatment only where needed, improving treatment efficiency while maintaining adequate coverage of target plants
Solution Approach 2:
The patent segments the treatment approach into individual plant-level applications rather than zone-level applications. This segmentation enables precise targeting of crops while avoiding weeds, improving treatment efficiency by eliminating unnecessary treatment of non-target areas
5Device complexity
If color based imaging is used to identify plants, then system simplicity is improved, but plant differentiation capability deteriorates
Solution Approach 1:
The patent changes the imaging parameter from simple color-based detection to active region-based detection that can incorporate multiple parameters. This maintains relative system simplicity while improving differentiation capability by focusing processing on relevant regions where detailed plant characteristics can be analyzed
Data Source
AI summary
A farming machine identifies and treats a plant as the farming machine travels through a field. The farming machine includes an array of tiled image sensors for capturing images of the field. A control system identifies an active region in the captured images and generates a tiled image that includes the active region. The control system applies image processing functions to identify the plant in the tiled image and actuates a treatment mechanism to treat the identified plant. The control system causes the array of image sensors to capture the image, identifies the plant, and actuates the treatment mechanism in real time as the farming machine travels through the field.