Digital Image Processing for Height Measurement Application Based on Python OpenCV and Regression Analysis

Abstract

Pixel is the smallest element given by the image from a digital camera and is used as a data source in the digital image processing process. In this paper, two data collection processes are carried out, i.e. taking actual height data using a standard stature meter and taking sample photos using a camera placed from the sample with a distance of 160 cm and a height of 100 cm. The sample photos obtained are then processed for segmentation of the sample body against the surrounding environment using several digital image-processing techniques such as grayscale, blur, edge detection, and bounding box in order to obtain a pixel value that represents the height of the sample. The next stage is the regression analysis process by correlating actual height with pixel height using five regression equation analysis methods such as least squares, logarithmic powers, exponentials, quadratic polynomials, and cubic polynomials. This study analyzes the differences between these methods in terms of correlation coefficient, Root Mean Squared Error (RMSE), average error, and accuracy between height calculation data based on digital image processing and actual height measurement data. From the results obtained, the logarithmic power method produces the best analytical value compared to other methods with the correlation coefficient, RMSE, average error percentage, and percentage accuracy of 0.976, 1.3, 0.58%, and 99.42%, respectively. While the cubic polynomial is in the last position, the correlation coefficient, RMSE, average error percentage, and accuracy percentage are 0.978, 1.41, 0.64%, and 99.36%, respectively.

Klasifikasi Tinggi Badan Menggunakan Metode Mask R-CNN

“…Abadi and Tahcfulloh [11] melakukan penelitian untuk mengukur tinggi badan dengan menggunakan beberapa metode digital image processing berbasis OpenCV seperti grayscale, blur, edge detection, dan bounding box untuk mengekstraksi pixel dari objek. Selain itu, penelitian ini membandingkan lima metode regression analysis seperti leasts squares, logarithmic powers, exponentials, quadratic polynomials, dan cubic polynomials untuk menganalisa korelasi antara tinggi badan berdasarkan pixel dengan tinggi badan actual dari objek.…”