Intensity-Based Image Preprocessing for Object Detection
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Solution Overview
Problem
Computer vision technologies face challenges in object detection and tracking due to reduced accuracy, increased resource consumption, and processing time, especially when objects are partially occluded, have complex structures, or similar visual characteristics, leading to difficulties in distinguishing objects within images.
Innovation Solution
A computer vision method that preprocesses images by adjusting light intensity values based on a defined threshold, increasing higher intensity pixels and reducing lower intensity pixels within a region of interest, to enhance contrast and accentuate object features, thereby improving object detection and tracking performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional image processing is used for object detection and tracking, then the system can process images, but accuracy is reduced when objects are partially occluded, have complex structures, or similar visual characteristics
Solution Approach 1:
The patent applies preliminary action by performing image preprocessing before object detection. The system adjusts light intensity values of pixels based on a threshold derived from the bounding box of the previously detected object, enhancing contrast and accentuating object features before the detection algorithm processes the image. This preliminary enhancement makes objects more distinguishable, particularly when they are partially occluded or have similar visual characteristics to background elements.
2Productivity
If traditional image processing is used, then processing can be performed, but resource consumption increases and processing time is extended
Solution Approach 1:
The patent applies local quality by selectively adjusting light intensity values only for pixels that fall within the bounding box region of the previously detected object. Instead of processing the entire image, the system focuses computational resources on the region of interest, thereby reducing overall processing time and resource consumption while still achieving enhanced object detection performance in the critical area.
3Measurement precision
If traditional image processing is used, then images can be processed, but accuracy is reduced for objects with similar visual characteristics
Solution Approach 1:
The patent applies parameter changes by modifying the light intensity parameter of pixels within the region of interest. The system increases light intensity values for pixels above a certain threshold and decreases them for pixels below the threshold, creating enhanced contrast that accentuates object features. This parameter transformation makes objects with similar visual characteristics more distinguishable by emphasizing their structural differences.
Data Source
AI summary
A computer vision method and computer vision system can be used to process a time-based series of images. For a subject image of the time-based series, a light intensity value is identified for each pixel of a set of pixels of the subject image. A light intensity threshold is defined for the subject image based on a size of a bounding region for an object detected within a previous image of the time-based series captured before the subject image. A modified image is generated for the subject image by one or both of: reducing the light intensity value of each pixel of a lower intensity subset of pixels of the subject image that is less than the light intensity threshold, and increasing the light intensity value of each pixel of a higher intensity subset of pixels of the subject image that is greater than the light intensity threshold.