Image Tracking Apparatus Using Segmented Color Region Detection
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Solution Overview
Problem
Existing image processing systems face challenges in accurately detecting and tracking objects in input images while maintaining high accuracy and efficiency, especially when the track object is partially blocked by obstacles, leading to increased processing time and power consumption.
Innovation Solution
An image processing apparatus with a track value setting portion, an auxiliary track value setting portion, and a track target detection portion that allows switching between track values and auxiliary track values to facilitate accurate detection by adjusting the signal values indicating the track object, thereby improving detection accuracy and reducing computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a plurality of colors of the track object are recognized together with positional relationships to detect the track object based on integral recognition, then detection accuracy is improved, but processing time and power consumption are increased
Solution Approach 1:
The patent divides the track object into multiple color regions (first color region and second color region) and processes each region separately through dedicated detection units. This segmentation allows the system to detect different colors independently rather than processing all colors simultaneously, reducing the computational complexity and processing time while maintaining detection accuracy.
Solution Approach 2:
The patent applies partial action by selectively processing only the necessary color regions for tracking. The system can choose to detect only the first color region or only the second color region depending on the situation, rather than always processing all color information. This reduces the amount of data processing required while still achieving accurate track object detection.
2Measurement precision
If a plurality of colors of the track object are recognized together with positional relationships to detect the track object based on integral recognition, then detection accuracy is improved, but device complexity is increased
Solution Approach 1:
The patent segments the detection process into separate detection units, each responsible for detecting specific color regions. This modular segmentation simplifies the overall device complexity by organizing the complex multi-color detection task into manageable, independent modules that can be processed separately rather than as a single complex integrated process.
Solution Approach 2:
The system performs partial detection by focusing on specific color regions rather than processing all color information simultaneously. This reduces the complexity of the detection process by limiting the scope of analysis to only the necessary color regions, making the overall system more manageable and less complex.
3Ease of operation
If the track object detection relies on a single track value, then processing simplicity is maintained, but detection accuracy decreases when the track object is blocked by obstacles
Solution Approach 1:
The patent changes the detection parameter from a single track value to multiple track values corresponding to different color regions. By setting track values for both the first color region and the second color region, the system can switch between different detection parameters depending on which region is visible, thereby maintaining detection accuracy even when the track object is partially blocked by obstacles.
Data Source
AI summary
A tracking process portion includes a search area setting portion for setting a search area in the input image, an image analysis portion for analyzing an image in the search area, an auxiliary track value setting portion for setting an auxiliary track value based on a result of the analysis, a track value setting portion for setting an auxiliary track value based on a result of the analysis and deciding whether the set track value is correct or not, and a track target detection portion for detecting a track object from the image in the search area based on the track value. If the set track value is incorrect, the track value setting portion performs a switching operation for setting the auxiliary track value and a track value.