Vision Sobel Edge

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Detects edges on the input image using Sobel kernel.

Library

Description

The Vision Sobel Edge block finds the edges on the input image and marks them in the output image using Sobel operator.

In order to use this block, be sure to follow the instructions described on the Vision Capture Image page, and take careful note of the limitations.

Input Ports

src_image

A handle to a source image that uses OpenCV (Open Source Computer Vision) IplImage structure.

Output Ports

edge_image

A grayscale image that marks the edges of input image in 8-bit format.

dst_image

Thresholded destination image in 8-bit gray or binary format.

err

An error signal which is negative in case of invalid memory allocation or usage of invalid parameter values.

Parameters and Dialog Box

Input image

Specifies the type of input image to be used for edge detection. The available options are Gray, Blue, Green, and Red. If the input image is a color image, this block either converts it into a grayscale image or splits it into red, green, or blue color plane according to the specified parameter. On the other hand, if the input is a grayscale or binary image, the edge detection algorithm is directly applied to it.

Order of derivative x

Specifies the order of derivative x.

Order of derivative y

Specifies the order of derivative y.

Kernel size

Specifies a kernel size of Sobel operator to be convolved with the input image. The Sobel operators combine Gaussian smoothing and differentiation for noise reduction. Gaussian smoothing, however, is not incorporated for kernel size 3×1 or 1×3. The following examples show Sobel operators for kernel size 3×3.

If Order of derivative x = 1 and Order of derivative y = 0, the operator is defined as

                |-1  0  1|
                |-2  0  2| .
                |-1  0  1|
            

If Order of derivative x = 0 and Order of derivative y = 1, the operator is defined as

                |-1 -2 -1|
                | 0  0  0|
                | 1  2  1|
                
                or
                
                | 1  2  1|
                | 0  0  0| .
                |-1 -2 -1|
            

The image derivative is calculated by convolving the image with the appropriate kernel:

edge_image(x,y) = dxorder+yordersrc_image/dxxorder•dyyorder |(x,y)

Threshold

Specifies a grayscale value for thresholding operation.

Threshold type

Specifies the type of thresholding to be used. The options are BINARY, BINARY_INV, TRUNC, TOZERO, and TOZERO_INV. The options are described as follows:

                BINARY:
                dst_image(x,y) = 255, if edge_image(x,y) > Threshold
                                 0, otherwise

                BINARY_INV:
                dst_image(x,y) = 0, if edge_image(x,y) > Threshold
                                 255, otherwise

                TRUNC:
                dst_image(x,y) = threshold, if edge_image(x,y) > Threshold
                                 edge_image(x,y), otherwise

                TOZERO:
                dst_image(x,y) = edge_image(x,y), if edge_image(x,y) > Threshold
                                 0, otherwise

                TOZERO_INV:
                dst_image(x,y) = 0, if edge_image(x,y) > Threshold
                                 edge_image(x,y), otherwise
            

Sample time

The sample time of the block. A sample time of 0 indicates that the block will be treated as a continuous time block. A positive sample time indicates that the block is a discrete time block with the given sample time. A sample time of -1 indicates that the block inherits its sample time.

Targets

See Also

• Vision Canny Edge
• Vision Laplace Edge

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