Rotation Matrix

Matrix is a Set of similar type of values. In mathematics, matrix is used in various applications like engineering mathematics, trigonometry, geometry, differential equation, etc. We can convert an object in 3D matrix into translate matrix or in the rotation matrix. Rotation Matrix is used in the pair of matrix. Translate matrix (T) and rotation matrix (R) when combines then they make transform matrix (Tr).
We can understand it by this formula:
                               R-T=Tr
Here R, T and Tr are in the form of matrix.
It is very easy to find the rotation matrix from the transform matrix but finding the translate matrix from transform matrix, is very difficult.
When we talk about pair of rotation matrix and combining this matrix just remind that last column of transform matrix should not be included. But in Translation Matrix we include the last column.
Let us discuss the properties of rotation matrix, rotational matrix, and matrix rotation:
Property 1: Rotational is a kind of an orthogonal matrix which has the property as if we multiply this matrix with its transpose matrix we will get the identical matrix. We can show it as:
                           RRT= I
Here RT is the transpose of the matrix and I is an identical matrix.
Property 2: If we find the sum of element of any row or column then we will get the sum as 1.
Property 3:  If we want to find the dot product of any two rows or column then it is always zero.
Property 4: In rotation matrix, rows of rotation matrix stand for coordinate which is in the original space.
Property 5: In rotation matrix, column stands for coordinates which is in rotated space.
We can use rotation matrix in 3D mathematics. If there is a matrix rotation, having three rows then row one will represent ‘right’, row two will represent upward direction and row three will represent the direction towards outside.