Package org.opencv.calib3d

Class StereoBM

  • public class StereoBM
extends StereoMatcher
    Class for computing stereo correspondence using the block matching algorithm, introduced and contributed to OpenCV by K. Konolige. This class implements a block matching algorithm for stereo correspondence, which is used to compute disparity maps from stereo image pairs. It provides methods to fine-tune parameters such as pre-filtering, texture thresholds, uniqueness ratios, and regions of interest (ROIs) to optimize performance and accuracy.

    • Constructor Detail

      • StereoBM

        protected StereoBM​(long addr)

    • Method Detail

      • __fromPtr__

        public static StereoBM __fromPtr__​(long addr)

      • getPreFilterType

        public int getPreFilterType()
        Gets the type of pre-filtering currently used in the algorithm.
        Returns:
        The current pre-filter type: 0 for PREFILTER_NORMALIZED_RESPONSE or 1 for PREFILTER_XSOBEL.

      • setPreFilterType

        public void setPreFilterType​(int preFilterType)
        Sets the type of pre-filtering used in the algorithm.
        Parameters:
        preFilterType - The type of pre-filter to use. Possible values are: - PREFILTER_NORMALIZED_RESPONSE (0): Uses normalized response for pre-filtering. - PREFILTER_XSOBEL (1): Uses the X-Sobel operator for pre-filtering. The pre-filter type affects how the images are prepared before computing the disparity map. Different pre-filtering methods can enhance specific image features or reduce noise, influencing the quality of the disparity map.

      • getPreFilterSize

        public int getPreFilterSize()
        Gets the current size of the pre-filter kernel.
        Returns:
        The current pre-filter size.

      • setPreFilterSize

        public void setPreFilterSize​(int preFilterSize)
        Sets the size of the pre-filter kernel.
        Parameters:
        preFilterSize - The size of the pre-filter kernel. Must be an odd integer, typically between 5 and 255. The pre-filter size determines the spatial extent of the pre-filtering operation, which prepares the images for disparity computation by normalizing brightness and enhancing texture. Larger sizes reduce noise but may blur details, while smaller sizes preserve details but are more susceptible to noise.

      • getPreFilterCap

        public int getPreFilterCap()
        Gets the current truncation value for prefiltered pixels.
        Returns:
        The current pre-filter cap value.

      • setPreFilterCap

        public void setPreFilterCap​(int preFilterCap)
        Sets the truncation value for prefiltered pixels.
        Parameters:
        preFilterCap - The truncation value. Typically in the range [1, 63]. This value caps the output of the pre-filter to [-preFilterCap, preFilterCap], helping to reduce the impact of noise and outliers in the pre-filtered image.

      • getTextureThreshold

        public int getTextureThreshold()
        Gets the current texture threshold value.
        Returns:
        The current texture threshold.

      • setTextureThreshold

        public void setTextureThreshold​(int textureThreshold)
        Sets the threshold for filtering low-texture regions.
        Parameters:
        textureThreshold - The threshold value. Must be non-negative. This parameter filters out regions with low texture, where establishing correspondences is difficult, thus reducing noise in the disparity map. Higher values filter more aggressively but may discard valid information.

      • getUniquenessRatio

        public int getUniquenessRatio()
        Gets the current uniqueness ratio value.
        Returns:
        The current uniqueness ratio.

      • setUniquenessRatio

        public void setUniquenessRatio​(int uniquenessRatio)
        Sets the uniqueness ratio for filtering ambiguous matches.
        Parameters:
        uniquenessRatio - The uniqueness ratio value. Typically in the range [5, 15], but can be from 0 to 100. This parameter ensures that the best match is sufficiently better than the next best match, reducing false positives. Higher values are stricter but may filter out valid matches in difficult regions.

      • getSmallerBlockSize

        public int getSmallerBlockSize()
        Gets the current size of the smaller block used for texture check.
        Returns:
        The current smaller block size.

      • setSmallerBlockSize

        public void setSmallerBlockSize​(int blockSize)
        Sets the size of the smaller block used for texture check.
        Parameters:
        blockSize - The size of the smaller block. Must be an odd integer between 5 and 255. This parameter determines the size of the block used to compute texture variance. Smaller blocks capture finer details but are more sensitive to noise, while larger blocks are more robust but may miss fine details.

      • getROI1

        public Rect getROI1()
        Gets the current Region of Interest (ROI) for the left image.
        Returns:
        The current ROI for the left image.

      • setROI1

        public void setROI1​(Rect roi1)
        Sets the Region of Interest (ROI) for the left image.
        Parameters:
        roi1 - The ROI rectangle for the left image. By setting the ROI, the stereo matching computation is limited to the specified region, improving performance and potentially accuracy by focusing on relevant parts of the image.

      • getROI2

        public Rect getROI2()
        Gets the current Region of Interest (ROI) for the right image.
        Returns:
        The current ROI for the right image.

      • setROI2

        public void setROI2​(Rect roi2)
        Sets the Region of Interest (ROI) for the right image.
        Parameters:
        roi2 - The ROI rectangle for the right image. Similar to setROI1, this limits the computation to the specified region in the right image.

      • create

        public static StereoBM create​(int numDisparities,
                              int blockSize)
        Creates StereoBM object
        Parameters:
        numDisparities - The disparity search range. For each pixel, the algorithm will find the best disparity from 0 (default minimum disparity) to numDisparities. The search range can be shifted by changing the minimum disparity.
        blockSize - The linear size of the blocks compared by the algorithm. The size should be odd (as the block is centered at the current pixel). Larger block size implies smoother, though less accurate disparity map. Smaller block size gives more detailed disparity map, but there is a higher chance for the algorithm to find a wrong correspondence.
        Returns:
        A pointer to the created StereoBM object. The function creates a StereoBM object. You can then call StereoBM::compute() to compute disparity for a specific stereo pair.

      • create

        public static StereoBM create​(int numDisparities)
        Creates StereoBM object
        Parameters:
        numDisparities - The disparity search range. For each pixel, the algorithm will find the best disparity from 0 (default minimum disparity) to numDisparities. The search range can be shifted by changing the minimum disparity.
        Returns:
        A pointer to the created StereoBM object. The function creates a StereoBM object. You can then call StereoBM::compute() to compute disparity for a specific stereo pair.

      • create

        public static StereoBM create()
        Creates StereoBM object
        Returns:
        A pointer to the created StereoBM object. The function creates a StereoBM object. You can then call StereoBM::compute() to compute disparity for a specific stereo pair.

      • finalize

        protected void finalize()
                 throws java.lang.Throwable
        Overrides:
        finalize in class StereoMatcher
        Throws:
        java.lang.Throwable