rectint

Rectangle intersection area

Syntax

area = rectint(A,B)

Description

area = rectint(A,B) returns the area of intersection of the rectangles specified by position vectors A and B.

If A and B each specify one rectangle, the output area is a scalar.

A and B can also be matrices, where each row is a position vector. area is then a matrix giving the intersection of all rectangles specified by A with all the rectangles specified by B. That is, if A is n-by-4 and B is m-by-4, then area is an n-by-m matrix where area(i,j) is the intersection area of the rectangles specified by the ith row of A and the jth row of B.

Note

A position vector is a four-element vector [x,y,width,height], where the point defined by x and y specifies one corner of the rectangle, and width and height define the size in units along the x and y axes respectively.

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

GPU Code Generation
Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.

Thread-Based Environment
Run code in the background using MATLAB® `backgroundPool` or accelerate code with Parallel Computing Toolbox™ `ThreadPool`.

This function fully supports thread-based environments. For more information, see Run MATLAB Functions in Thread-Based Environment.

GPU Arrays
Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

The rectint function fully supports GPU arrays. To run the function on a GPU, specify the input data as a gpuArray (Parallel Computing Toolbox). For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).

Distributed Arrays
Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.

This function fully supports distributed arrays. For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).

Version History

Introduced before R2006a

rectint

Syntax

Description

Extended Capabilities

C/C++ Code Generation Generate C and C++ code using MATLAB® Coder™.

GPU Code Generation Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.

Thread-Based Environment Run code in the background using MATLAB® backgroundPool or accelerate code with Parallel Computing Toolbox™ ThreadPool.

GPU Arrays Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.