Documentation

# 2-D Standard Deviation

Find standard deviation of each input matrix

## Library

Statistics

`visionstatistics` ## Description

The Standard Deviation block computes the standard deviation of each row or column of the input, along vectors of a specified dimension of the input, or of the entire input. The Standard Deviation block can also track the standard deviation of a sequence of inputs over a period of time. The Running standard deviation parameter selects between basic operation and running operation.

### Port Description

PortSupported Data Types

Input

• Double-precision floating point

• Single-precision floating point

Reset

• Double-precision floating point

• Single-precision floating point

• Boolean

• 8-, 16-, and 32-bit signed integers

• 8-, 16-, and 32-bit unsigned integers

ROI

Rectangles and lines:

• Double-precision floating point

• Single-precision floating point

• Boolean

• 8-, 16-, and 32-bit signed integers

• 8-, 16-, and 32-bit unsigned integers

• Boolean

Label

• 8-, 16-, and 32-bit unsigned integers

Label Numbers

• 8-, 16-, and 32-bit unsigned integers

Output

• Double-precision floating point

• Single-precision floating point

Flag

• Boolean

### Basic Operation

When you do not select the Running standard deviation check box, the block computes the standard deviation of each row or column of the input, along vectors of a specified dimension of the input, or of the entire input at each individual sample time, and outputs the array y. Each element in y contains the standard deviation of the corresponding column, row, vector, or entire input. The output y depends on the setting of the Find the standard deviation value over parameter. For example, consider a 3-dimensional input signal of size M-by-N-by-P:

• `Entire input` — The output at each sample time is a scalar that contains the standard deviation of the entire input.

```y = std(u(:)) % Equivalent MATLAB code ```
• `Each Row` — The output at each sample time consists of an M-by-1-by-P array, where each element contains the standard deviation of each vector over the second dimension of the input. For an input that is an M-by-N matrix, the output at each sample time is an M-by-1 column vector.

```y = std(u,0,2) % Equivalent MATLAB code ```
• `Each Column` — The output at each sample time consists of a 1-by-N-by-P array, where each element contains the standard deviation of each vector over the first dimension of the input. For an input that is an M-by-N matrix, the output at each sample time is a 1-by-N row vector.

```y = std(u,0,1) % Equivalent MATLAB code ```

In this mode, the block treats length-M unoriented vector inputs as M-by-1 column vectors.

• `Specified Dimension` — The output at each sample time depends on Dimension. If Dimension is set to `1`, the output is the same as when you select `Each column`. If Dimension is set to `2`, the output is the same as when you select `Each row`. If Dimension is set to `3`, the output at each sample time is an M-by-N matrix containing the standard deviation of each vector over the third dimension of the input.

```y = std(u,0,Dimension) % Equivalent MATLAB code ```

For purely real or purely imaginary inputs, the standard deviation of the jth column of an M-by-N input matrix is the square root of its variance:

For complex inputs, the output is the total standard deviation, which equals the square root of the total variance, or the square root of the sum of the variances of the real and imaginary parts. The standard deviation of each column in an M-by-N input matrix is given by:

`${\sigma }_{j}=\sqrt{{\sigma }_{j,\mathrm{Re}}^{2}+{\sigma }_{j,\mathrm{Im}}^{2}}$`

### Note

The total standard deviation does not equal the sum of the real and imaginary standard deviations.

### Running Operation

When you select the Running standard deviation check box, the block tracks the standard deviation of successive inputs to the block. In this mode, the block treats each element as a channel.

### Resetting the Running Standard Deviation

The block resets the running standard deviation whenever a reset event is detected at the optional `Rst` port. The reset sample time must be a positive integer multiple of the input sample time.

You specify the reset event in the Reset port parameter:

• `None` disables the `Rst` port.

• `Rising edge` — Triggers a reset operation when the `Rst` input does one of the following:

• Rises from a negative value to a positive value or zero

• Rises from zero to a positive value, where the rise is not a continuation of a rise from a negative value to zero (see the following figure) • `Falling edge` — Triggers a reset operation when the `Rst` input does one of the following:

• Falls from a positive value to a negative value or zero

• Falls from zero to a negative value, where the fall is not a continuation of a fall from a positive value to zero (see the following figure) • `Either edge` — Triggers a reset operation when the `Rst` input is a ```Rising edge``` or `Falling edge` (as described earlier)

• `Non-zero sample` — Triggers a reset operation at each sample time that the `Rst` input is not zero

### Note

When running simulations in the Simulink® MultiTasking mode, reset signals have a one-sample latency. Therefore, when the block detects a reset event, there is a one-sample delay at the reset port rate before the block applies the reset.

## ROI Processing

To calculate the statistical value within a particular region of interest (ROI) of the input, select the Enable ROI processing check box. This option is only available when the Find the standard deviation value over parameter is set to ```Entire input``` and the Running standard deviation check box is not selected. ROI processing is only supported for 2-D inputs.

Use the ROI type parameter to specify whether the ROI is a rectangle, line, label matrix, or binary mask. A binary mask is a binary image that enables you to specify which pixels to highlight, or select. In a label matrix, pixels equal to 0 represent the background, pixels equal to 1 represent the first object, pixels equal to 2 represent the second object, and so on. When the ROI type parameter is set to `Label matrix`, the Label and Label Numbers ports appear on the block. Use the Label Numbers port to specify the objects in the label matrix for which the block calculates statistics. The input to this port must be a vector of scalar values that correspond to the labeled regions in the label matrix. For more information about the format of the input to the ROI port when the ROI is a rectangle or a line, see the Draw Shapes block reference page.

For rectangular ROIs, use the ROI portion to process parameter to specify whether to calculate the statistical value for the entire ROI or just the ROI perimeter.

Use the Output parameter to specify the block output. The block can output separate statistical values for each ROI or the statistical value for all specified ROIs. This parameter is not available if, for the ROI type parameter, you select `Binary mask`.

If, for the ROI type parameter, you select `Rectangles` or `Lines`, the Output flag indicating if ROI is within image bounds check box appears in the dialog box. If you select this check box, the Flag port appears on the block. The following tables describe the Flag port output based on the block parameters.

Output = Individual statistics for each ROI

Flag Port OutputDescription
0ROI is completely outside the input image.
1ROI is completely or partially inside the input image.

Output = Single statistic for all ROIs

Flag Port OutputDescription
0All ROIs are completely outside the input image.
1At least one ROI is completely or partially inside the input image.

If the ROI is partially outside the image, the block only computes the statistical values for the portion of the ROI that is within the image.

If, for the ROI type parameter, you select ```Label matrix```, the Output flag indicating if input label numbers are valid check box appears in the dialog box. If you select this check box, the Flag port appears on the block. The following tables describe the Flag port output based on the block parameters.

Output = Individual statistics for each ROI

Flag Port OutputDescription
0Label number is not in the label matrix.
1Label number is in the label matrix.

Output = Single statistic for all ROIs

Flag Port OutputDescription
0None of the label numbers are in the label matrix.
1At least one of the label numbers is in the label matrix.

## Parameters

Running standard deviation

Enables running operation when selected.

Reset port

Specify the reset event that causes the block to reset the running standard deviation. The sample time of the input to the Rst port must be a positive integer multiple of the input sample time. This parameter appears only when you select the Running standard deviation check box. For more information, see Resetting the Running Standard Deviation.

Find the standard deviation value over

Specify whether to find the standard deviation value along rows, columns, entire input, or the dimension specified in the Dimension parameter. For more information, see Basic Operation.

Dimension

Specify the dimension (one-based value) of the input signal, over which the standard deviation is computed. The value of this parameter cannot exceed the number of dimensions in the input signal. This parameter is only visible when the Find the standard deviation value over parameter is set to `Specified dimension`.

Enable ROI Processing

Select this check box to calculate the statistical value within a particular region of each image. This parameter is only available when the Find the standard deviation value over parameter is set to `Entire input`, and the block is not in running mode.

ROI type

Specify the type of ROI you want to use. Your choices are `Rectangles`, `Lines`, ```Label matrix```, or `Binary mask`.

ROI portion to process

Specify whether you want to calculate the statistical value for the entire ROI or just the ROI perimeter. This parameter is only visible if, for the ROI type parameter, you specify `Rectangles`.

Output

Specify the block output. The block can output a vector of separate statistical values for each ROI or a scalar value that represents the statistical value for all the specified ROIs. This parameter is not available if, for the ROI type parameter, you select `Binary mask`.

Output flag indicating if ROI is within image bounds

When you select this check box, a Flag port appears on the block. For a description of the Flag port output, see the tables in ROI Processing.

Output flag indicating if label numbers are valid

When you select this check box, a Flag port appears on the block. This check box is visible only when you select ```Label matrix``` for the ROI type parameter. For a description of the Flag port output, see the tables in ROI Processing.

## Example The ex_vision_2dstd calculates the standard deviation value within two ROIs.

 2-D Mean Computer Vision Toolbox™ 2-D Variance Computer Vision Toolbox `std` MATLAB