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# Translate

Translate image in 2-D plane using displacement vector

## Library

Geometric Transformations

`visiongeotforms`

## Description

Use the Translate block to move an image in a two-dimensional plane using a displacement vector, a two-element vector that represents the number of pixels by which you want to translate your image. The block outputs the image produced as the result of the translation.

Note

This block supports intensity and color images on its ports.

PortInput/OutputSupported Data TypesComplex Values Supported

Image / Input

M-by-N matrix of intensity values or an M-by-N-by-P color video signal where P is the number of color planes

• Double-precision floating point

• Single-precision floating point

• Fixed point

• 8-, 16-, 32-bit signed integer

• 8-, 16-, 32-bit unsigned integer

No

Offset

Vector of values that represent the number of pixels by which to translate the image

Same as I port

No

Output

Translated image

Same as I port

No

The input to the Offset port must be the same data type as the input to the Image port. The output is the same data type as the input to the Image port.

Use the Output size after translation parameter to specify the size of the translated image. If you select `Full`, the block outputs a matrix that contains the entire translated image. If you select `Same as input image`, the block outputs a matrix that is the same size as the input image and contains a portion of the translated image. Use the Background fill value parameter to specify the pixel values outside the image.

Use the Offset source parameter to specify how to enter your displacement vector. If you select `Specify via dialog`, the Offset parameter appears in the dialog box. Use it to enter your displacement vector, a two-element vector, `[r c]`, of real, integer values that represent the number of pixels by which you want to translate your image. The `r` value represents how many pixels up or down to shift your image. The `c` value represents how many pixels left or right to shift your image. The axis origin is the top-left corner of your image. For example, if you enter `[2.5 3.2]`, the block moves the image 2.5 pixels downward and 3.2 pixels to the right of its original location. When the displacement vector contains fractional values, the block uses interpolation to compute the output.

Use the Interpolation method parameter to specify which interpolation method the block uses to translate the image. If you translate your image in either the horizontal or vertical direction and you select ```Nearest neighbor```, the block uses the value of the nearest pixel for the new pixel value. If you translate your image in either the horizontal or vertical direction and you select `Bilinear`, the new pixel value is the weighted average of the four nearest pixel values. If you translate your image in either the horizontal or vertical direction and you select `Bicubic`, the new pixel value is the weighted average of the sixteen nearest pixel values.

The number of pixels the block considers affects the complexity of the computation. Therefore, the nearest-neighbor interpolation is the most computationally efficient. However, because the accuracy of the method is roughly proportional to the number of pixels considered, the bicubic method is the most accurate.

If, for the Output size after translation parameter, you select `Full`, and for the Offset source parameter, you select `Input port`, the Maximum offset parameter appears in the dialog box. Use the Maximum offset parameter to enter a two-element vector of real, scalar values that represent the maximum number of pixels by which you want to translate your image. The block uses this parameter to determine the size of the output matrix. If the input to the Offset port is greater than the Maximum offset parameter values, the block saturates to the maximum values.

If, for the Offset source parameter, you select `Input port`, the Offset port appears on the block. At each time step, the input to the Offset port must be a vector of real, scalar values that represent the number of pixels by which to translate your image.

### Fixed-Point Data Types

The following diagram shows the data types used in the Translate block for bilinear interpolation of fixed-point signals.

You can set the product output, accumulator, and output data types in the block mask as discussed in the next section.

## Parameters

Output size after translation

If you select `Full`, the block outputs a matrix that contains the translated image values. If you select ```Same as input image```, the block outputs a matrix that is the same size as the input image and contains a portion of the translated image.

Offset source

Specify how to enter your translation parameters. If you select `Specify via dialog`, the Offset parameter appears in the dialog box. If you select `Input port`, port O appears on the block. The block uses the input to this port at each time step as your translation values.

Offset source

Enter a vector of real, scalar values that represent the number of pixels by which to translate your image.

Background fill value

Specify a value for the pixels that are outside the image.

Interpolation method

Specify which interpolation method the block uses to translate the image. If you select `Nearest neighbor`, the block uses the value of one nearby pixel for the new pixel value. If you select `Bilinear`, the new pixel value is the weighted average of the four nearest pixel values. If you select `Bicubic`, the new pixel value is the weighted average of the sixteen nearest pixel values.

The number of pixels the block considers affects the complexity of the computation. Therefore, the `Nearest-neighbor` interpolation is the most computationally efficient. However, because the accuracy of the method is proportional to the number of pixels considered, the `Bicubic` method is the most accurate.

Maximum offset

Enter a vector of real, scalar values that represent the maximum number of pixels by which you want to translate your image. This parameter must have the same data type as the input to the Offset port. This parameter is visible if, for the Output size after translation parameter, you select `Full` and, for the Offset source parameter, you select `Input port`.

Rounding mode

Select the rounding mode for fixed-point operations.

Overflow mode

Select the overflow mode for fixed-point operations.

Offset values

Choose how to specify the word length and the fraction length of the offset values.

• When you select ```Same word length as input```, the word length of the offset values match that of the input to the block. In this mode, the fraction length of the offset values is automatically set to the binary-point only scaling that provides you with the best precision possible given the value and word length of the offset values.

• When you select `Specify word length`, you can enter the word length of the offset values, in bits. The block automatically sets the fraction length to give you the best precision.

• When you select `Binary point scaling`, you can enter the word length and the fraction length of the offset values, in bits.

• When you select `Slope and bias scaling`, you can enter the word length, in bits, and the slope of the offset values. The bias of all signals in the Computer Vision Toolbox™ blocks is 0.

This parameter is visible if, for the Offset source parameter, you select `Specify via dialog`.

Product output

As depicted in the previous figure, the output of the multiplier is placed into the product output data type and scaling. Use this parameter to specify how to designate this product output word and fraction lengths.

• When you select `Same as first input`, these characteristics match those of the first input to the block.

• When you select `Binary point scaling`, you can enter the word length and the fraction length of the product output, in bits.

• When you select `Slope and bias scaling`, you can enter the word length, in bits, and the slope of the product output. The bias of all signals in the Computer Vision Toolbox blocks is 0.

Accumulator

As depicted in the previous figure, inputs to the accumulator are cast to the accumulator data type. The output of the adder remains in the accumulator data type as each element of the input is added to it. Use this parameter to specify how to designate this accumulator word and fraction lengths.

• When you select `Same as product output`, these characteristics match those of the product output.

• When you select `Same as first input`, these characteristics match those of the first input to the block.

• When you select `Binary point scaling`, you can enter the word length and the fraction length of the accumulator, in bits.

• When you select `Slope and bias scaling`, you can enter the word length, in bits, and the slope of the accumulator. The bias of all signals in the Computer Vision Toolbox blocks is 0.

Output

Choose how to specify the word length and fraction length of the output of the block:

• When you select `Same as first input`, these characteristics match those of the first input to the block.

• When you select `Binary point scaling`, you can enter the word length and the fraction length of the output, in bits.

• When you select `Slope and bias scaling`, you can enter the word length, in bits, and the slope of the output. The bias of all signals in the Computer Vision Toolbox blocks is 0.

Lock data type settings against change by the fixed-point tools

Select this parameter to prevent the fixed-point tools from overriding the data types you specify on the block mask. For more information, see `fxptdlg` (Fixed-Point Designer), a reference page on the Fixed-Point Tool in the Simulink® documentation.

## References

[1] Wolberg, George. Digital Image Warping. Washington: IEEE Computer Society Press, 1990.

## See Also

 Resize Computer Vision Toolbox software Rotate Computer Vision Toolbox software Shear Computer Vision Toolbox software

expand all

## Extended Capabilities

### C/C++ Code GenerationGenerate C and C++ code using Simulink® Coder™.

Introduced before R2006a

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