VECTOR_INNER_PRODUCT_CVIP

vector_inner_product_cvip() - calculates the normalized vector inner product similarity metric between two feature vectors

SYNTAX
DESCRIPTION
REFERENCE
EXAMPLE
CREDITS

SYNTAX

d =  vector_inner_product_cvip( vector1, vector2)

Input Parameters include :

vector1 - Feature vector 1. A numeric array of n elements.
vector2 - Feature vector 2. A numeric array of n elements.

Output Parameter include :

d - The normalized vector inner product similarity metric between vector1 and vector2

DESCRIPTION

This function calculates the normalized vector inner product between the two input feature vector. The vector inner product is a similarity measure used to assess the amount of similarity between two feature vectors.

The vector inner product is defined for vectors x and y as:

$x \cdot y = \frac{\sum_{i=1}^n x_i y_i}{\big ( \sum_{i=1}^n x_i^2 \big)^{1/2} \cdot \big( \sum_{i=1}^n y_i^2 \big)^{1/2}}$

REFERENCE

1. Scott E Umbaugh. DIGITAL IMAGE PROCESSING AND ANALYSIS: Applications with MATLAB and CVIPtools, 3rd Edition.

EXAMPLE

% Input vectors

 vector1 = [1 3 4 2];

 vector2 = [-3 3.2 sqrt(2) pi];

% calling function

 d =  vector_inner_product_cvip( vector1, vector2)

d =

    0.6069

VECTOR_INNER_PRODUCT_CVIP

Contents

SYNTAX

DESCRIPTION

REFERENCE

EXAMPLE

CREDITS