Chrominance Histogram Segmentation With Dynamic Thresholding
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Solution Overview
Problem
Existing color image segmentation methods based on fixed thresholds or color ranges often lead to false segmentation and misjudgment.
Innovation Solution
An image segmentation method based on chrominance components, involving obtaining a chrominance component, generating a histogram, identifying peaks and troughs, and determining a dynamic segmentation threshold to segment images into regions with different chrominances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a fixed threshold or color range is used for segmentation, then the segmentation process is simple and fast, but false segmentation and misjudgment occur frequently
Solution Approach 1:
The patent applies the dynamics principle by transforming the fixed threshold into a dynamic threshold that adapts to different images. The system automatically determines segmentation thresholds based on the statistical characteristics (histogram peaks and valleys) of each input image's chrominance component, allowing the threshold to vary dynamically rather than remaining fixed, thereby resolving the contradiction between simplicity and accuracy
Solution Approach 2:
The patent employs parameter changes by modifying the threshold parameter from a fixed value to a dynamically determined value based on image-specific characteristics. By analyzing the chrominance histogram and identifying peak-valley patterns, the system adjusts the segmentation threshold parameter adaptively, improving segmentation reliability while maintaining operational efficiency
2Reliability
If a dynamic threshold based on histogram analysis is used, then segmentation accuracy improves, but the computational complexity increases
Solution Approach 1:
The patent applies the extraction principle by isolating and analyzing only the chrominance component of the image, separating it from other components. By focusing computational resources on extracting and analyzing the chrominance histogram specifically, rather than processing the entire image or all color components, the system reduces overall computational complexity while maintaining high segmentation accuracy
Solution Approach 2:
The patent employs segmentation by dividing the chrominance histogram analysis into distinct stages: generating the histogram, identifying peaks and valleys, and determining thresholds based on these features. This segmented approach to histogram analysis breaks down the complex computation into manageable steps, reducing overall computational burden while achieving accurate segmentation
Data Source
AI summary
The present disclosure relates to an image segmentation method based on a chrominance component. The method includes the following steps: obtaining a chrominance component of an image; generating a chrominance component histogram according to the chrominance component; determining peaks and troughs in the chrominance component histogram according to a preset chrominance interval and preset peak and trough setting conditions; obtaining a segmentation threshold according to the peaks and the troughs; and segmenting the image into a plurality of regions with different chrominances according to the segmentation threshold. In the present disclosure, the segmentation threshold is obtained according to the peaks and the troughs, the segmentation threshold is dynamically adjusted according to different images, and a fixed segmentation threshold is not used, thereby effectively reducing false segmentation.