Body Mass Index Measurement System using Image Processing

Abdullah Sani and Elsa Agatya Marlin

Department of electrical Engineering, Politeknik Negeri Batam, Batam, Indonesia

Keywords: Image Processing, Broca Formula, Body Mass Index.

Abstract: In general, to know the ideal body weight, one must first weigh the weight and measure its height manually.

After that do the calculations with certain mathematical formulas so that a conclusion about the condition is

ideal body weight. However, it is less efficient especially if applied in bulk. Therefore, the author will create

a system with the Image Processing application in real-time using the webcam by specifying the height and

width of the body at a specific distance and scale that applies the calculation of the value of the pixel values

where the pixel value is as a reference as a variable function to obtain the person's height and weight estimate.

Then after gaining height and weight than the calculation of Body Mass Index with Broca formula to be useful

as an identification system in effectively measuring human body mass index. This system can be used as a

system that can require humans to more efficient time and reduce human error. The output generated from

this system is the high value, weight, and BMI values of the person's body whether the condition is ideal or

not.

1 INTRODUCTION

This In the current era of developments, various

human-created technologies are required to be more

effective, fast, and easy in assisting human work in

the areas of health, information, communication, and

other areas. The more technology used is the more

practical human work. The Discovery and

development of new technologies are expected to

bring a positive impact on human life in all things

more efficiently (Triyandi, 2014).

The identification system of a person does not

escape the technological developments that occurred

in the present era. Such an identification system can

be a measurement of the human body by utilizing

high parameters and weight gain (Wicaksana 2016).

By utilizing these parameters, one can identify and

know the condition of the body is ideal or not. In

general, to know the ideal body weight, one must first

perform the measurements manually. After that do

the calculations with certain mathematical formulas

so that a conclusion about the condition is ideal body

weight. However, there are still many people who

rarely control their weight regularly, while it is very

important to know whether the condition of the body

is good or not in the weight and height, especially if

applied in bulk because it will require a lot of

weighing and measuring tools as well as long enough

time for its use (Efendi, 2017).

It is therefore created a system in real-time using

the webcam by specifying the height and width of the

body at a specified distance and scale that applies the

calculation of the pixel value in which the pixel value

is referenced as a variable function to obtain the

person's height and weight estimate.

Then after gaining height and weight, the

calculation of Body Mass Index with Broca formula

to be useful as an identification system in measuring

the human body mass index.

2 BASIC UNDERSTANDING

2.1 Image Processing

Image processing or image processing is a method to

better improve the image quality by utilizing several

methods of image processing itself, such as the setting

on the color or image size. Image processing is widely

utilized to detect an object, where input from the

image processing can be a photo or motion picture in

real-time, while the output can be a parameter related

to imagery such as the pixel value in the image

detected according to its needs (Putri, 2016).

Sani, A. and Marlin, E.

Body Mass Index Measurement System using Image Processing.

DOI: 10.5220/0010352000810084

In Proceedings of the 3rd International Conference on Applied Engineering (ICAE 2020), pages 81-84

ISBN: 978-989-758-520-3

Research is conducted by implementing the

image processing system in the calculation process,

where when a person's body is faced with the camera,

the camera will detect the image (tracking) and then

determine the point of the coordinate until finally

obtained the high value and width of the pixel used as

a reference in the calculation.

2.1.1 RGB Image

The RGB image or color image is a digital image

composed of 3 main colors, namely red, green, and

blue. Meanwhile, in an image, other colors are the

result of the combination of the three main colors

(Makalalang, 2012). RGB color concepts can be

shown in Figure 1 RGB Color Concepts.

2.1.2 Blob Counter

Blob Counter is a method of image processing used

to calculate, filter, and extract objects contained in an

image by mapping the object to obtain the dimensions

or size of the desired object. The principle is to nod

all the pixels that have a value less than the same as

the background pixel value as the background of the

object. Thus the pixel that has the value above the

background pixel value will be considered as the

object. The mapping is then done to distinguish

between the background and object (Uma, 2010).

2.1.3 Broca Formula

The BROCA formula is a formula used to determine the

ideal body weight by simply utilizing the height

measurement parameters (Hutabarat, 2016). In this

study, using a formula of Broca that is utilized to get the

value of a person's ideal weight and also is one as a point

of reference to get the value of weight prediction from

the detected body. Here is the Broca formula

Ideal BW







Body Height





-100







Body Height





-100



×10%



(1)

Figure 1: RGB color concepts (Makalalang, 2012).

2.1.4 Body Mass Index

Body Mass Index is an indicator to determine the

bodyweight of a person whether it has a body that is

too thin, ideal, or too fat and is a good measurement

way to assess the risk of illness that can occur due to

an unideal weight, by utilizing the height parameters

in meters and weight in units Kg (Saffana, 2018;

Andre, 2016; Heriansyah, 2017). The formula of the

body mass index calculation can be seen in Equation

(2).

BMI=

Body Weight





Bod

Hei





×Bod

Hei





(2)

From the result of the calculation, it is obtained by

classifying the percentage of whether a person's

weight is too thin, ideal, or too fat. The classifications

can be seen in Table 1. BMI Value Classification.

3 PROPOSED METHOD

In Figure 2, the first step is to do an acquisition of an

image to the object (human body) in a full body in a

standing position. This process is conducted with a

distance of 300 cm against the object as well as a

camera height 80 cm from the floor. In the detection

process, the camera will look for the object in real -

time, where the rectangle will enlarge or shrink

according to the detected object, and the result of the

pixel coordinate value will also change according to

the rectangle size, after the stable rectangle, then

capture the image to make it easier for someone to

know the body mass index.

When the object has been captured by the camera,

the program will then perform its approximate height

and width calculation using pixel value calculations.

Where to use the calculation formula as follows:

Body Height Prediction





Pixel Heigh

-Average(Error Pixel Height)

(3)

Body Width Prediction





Pixel Width-Average(Error Pixel Width)

(4)

Table 1: BMI value classification.

Nutritional Status BMI

Weight deficiency < 18,5

Ideal 18,5

–

24,9

Excess weight 25

–

Fat 30

–

Fat unhealth

> 40

ICAE 2020 - The International Conference on Applied Engineering

Figure 2: Flowchart system.

After the approximate value of height and width

of the body in cm, the next step is to do the calculation

of Ideal body weight with Broca formula as in

Equation 1. The next step is to determine the

approximate weight value of the body by utilizing the

height and width parameters, as well as the ideal

weight value. The calculation formula is as presented

in Equation (5). After obtaining the high prediction

and weight parameters, the Body Mass Index (BMI)

calculation with the calculation of the formula

corresponds to equation (2).

Body Weight Prediction





Average∆

BH-BWi

-BH-BWi

+BW Ideal(Kg)

(5)

B.H (cm): Height prediction value in cm units.

Average (Error Pixel Height): The average value

of pixel high error obtained from sample data.

Average (Error Pixel Width): The average value

of of pixel width error obtained from sample

data.

Average (∆

B.H-B.Wi

): The average value of

difference from the height prediction and boody

width obtained from sample data.

(B.H – B.Wi): Delta value in height prediction and

width prediction of body detected.

4 RESULT AND DISCUSSION

4.1 Data Retrieval

At the beginning of the study, cropping on the image

filtering results by removing the background from the

image so that only the remaining objects will be

detected and then calculated. Filtering is done by

setting the RGB parameter, in this research the RGB

value is set to the value R = 222, G = 89, B = 83, then

the RGB filtering result image in the filter returned to

binary to get the intact object image so that it is easy

to detect by the BLOB counter. The result of the

BLOB counter can be shown in Figure 3.

4.2 Determination Equation of

Calculation

The determination of the equation of calculation in

this research is conducted by taking some sample

objects (human body) which are used as the

calculation of height and width estimate of the body.

Sample data is taken in the form of height, shoulder

width, and actual weight and calculation of the ideal

weight gained from the actual height and weight. The

comparison is conducted by retrieving the sample

data of the height and width pixel on the tracking

result object on the camera. The result of the

calculation will be recorded for further analysis.

The obtained data is calculated to determine the

ideal weight value of a person by processing the

existing parameters. The average value of the error at

the height of the pixel and the average value of the

error at the pixel width can be used as a reference to

get the height and width predicted value of the human

body detected by the camera. In the study, 30 human

objects were used as samples to determine the

average error value, and the value obtained for is 64.5

for the average height error and 2.25 for the average

error width of the body. Determination of calculations

to get high prediction values and width of the body

can be seen in equations 3 and 4. The following Table

2 is the result of the high and wide prediction

calculation of the body. The prediction of person's

weight prediction could be calculated using Equation

(5). The calculation results are presented in Table 3

and Table 4.

Body Mass Index Measurement System using Image Processing

Figure 3: Blob counter detection results.

Table 2: Results of height and width prediction calculation.

H.B

Pre.

Error

B.Wi

Pre.

Error

No

Name

Act

H.B

Act

B.Wi

(cm)

(cm)

(cm)

(cm)

1

Alin

165,0

165,6

0,6

40,0

36,8

3,3

2

Arya

173,0

176,6

3,6

41,0

38,8

2,3

3

Bunga

156,0

161,6

5,6

37,0

36,8

0,3

4

Cindy

162,0

158,6

3,4

40,0

35,8

4,3

5

Dita

160,0

155,6

4,4

34,0

33,8

0,3

6

Erin

156,0

149,6

6,4

38,0

36,8

1,3

7

Ilmi

160,0

157,6

2,4

43,0

40,8

2,3

8

Ipen

166,0

167,6

1,6

46,0

44,8

1,3

9

Limcol

168,0

169,6

1,6

42,0

40,8

1,3

10

Maul

174,0

180,6

6,6

43,0

38,8

4,3

Table 3: Calculation results on sample data.

Table 4: Calculation results on sample data

5 CONCLUSIONS

Based on the results and analysis that has been done

in the study can be concluded that the system can

work with an average percentage of the body's high

error rate of 4.1% and weight by 8.6 and the distance,

color, and clothing used by the measured object

greatly affect the outcome of the image.

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ICAE 2020 - The International Conference on Applied Engineering