LibHoughTransform
This is a library implementing the Linear Hough Transform for feature extraction from 2D image data. It provides a factory function to create Hough transform objects that detect straight lines in binary images and return line parameters (slope and intercept). The library is designed as a reusable component for pattern recognition tasks, not as a standalone trading EA.
Open the interactive view (equity curve, symbol switch)Key facts
Backtest results (H1, about 1 year)
Not backtested yet — this EA could not be converted automatically.
Strategy analysis
This code is not a trading strategy but a Hough Transform mathematical library for line detection in image processing. The core concept of the Hough Transform maps points from image space to parameter space, finding collinear point sets through a voting mechanism. Entry conditions are not applicable here, as the library function accepts a HoughImage input and iterates over all non-zero pixels to accumulate votes in parameter space. Exit conditions are likewise not applicable, but the extraction process uses the findMax function to sequentially find the parameter points with the highest vote counts, zeroing out the peak neighborhood to avoid duplicate detections. Position sizing and money management are completely absent as this is a utility library. The library supports template instantiation with int and double data types, creates objects via the createHoughTransform factory function, and can extract parameters for up to 8 lines. The parameter space quantizes the angle range from 0 to π into size discrete values, with the distance range automatically calculated based on the image diagonal length.
Strengths
- Template-based design supports multiple data types for reuse, providing strong code generality
- Factory pattern for object creation decouples interface from implementation, facilitating extension of more transform types
- Pre-computed trigonometric values stored in a lookup table avoid redundant calculations, improving runtime efficiency
- Peak neighborhood zeroing mechanism effectively prevents duplicate detection of the same line
- Provides getHoughInfo meta-information function for library users to understand output parameter meanings
Weaknesses
- findMax function performs linear scan of the entire parameter space each time, O(n²) complexity, inefficient for large quantization sizes
- Lacks boundary validation for input image dimensions and quants parameter, potentially causing array out-of-bounds or memory overflow
- Insufficient numerical stability handling when MathSin(y*d) approaches zero, potentially producing extremely large or inaccurate parameter values
- Only implements linear Hough Transform without support for circle detection or other shape detection, limited functionality
- The loop variable i in extract function may cause counting errors when early returns and continue statements interact
Possible improvements
- Optimize findMax to maintain an ordered structure or use more efficient peak detection algorithms to reduce time complexity for multiple extractions
- Add input parameter validation and exception handling, including quants range checks, image dimension verification, and divide-by-zero protection
- Support more Hough Transform variants such as circle detection and generalized Hough Transform to broaden the library's applicability
Risk assessment
Overall risk: Safe
- This library does not involve trading operations, no financial risk
- Numerical computation has divide-by-zero and overflow hazards that may produce invalid results under extreme inputs
Evaluation scores
Parameters
| Parameter | Default | Description |
|---|---|---|
quants | N/A (constructor param) | Quantization parameter for Hough transform angle and distance resolution |
type | TYPE_INT | Data type selection (TYPE_INT or TYPE_DOUBLE) |
lines | 8 | Number of detected lines; 2 parameters per line |
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Backtests are historical simulations and do not guarantee future results. Not financial advice.