A Customer profiling system using image processing for stock management in apparel stores

Date of Publication


Document Type

Bachelor's Thesis

Degree Name

Bachelor of Science in Electronics and Communications Engineering


Gokongwei College of Engineering


Electronics And Communications Engg

Thesis Adviser

Edwin Sybingco

Defense Panel Chair

Reggie C. Gustilo

Defense Panel Member

Argel A. Bandala
Mark Lorenze D. Torregoza


Customer profiling is a marketing strategy that helps in identifying and knowing the customers’ needs and demands. Customer profiling is based on building common definitions that groups of people will fit into. Through customer profiling, business concepts can be projected, and be assessed if it will meet the market’s demands. Also, identifying the target market through its demographics, and buying and spending habits, business owners will be able to project and implement their marketing and advertising efforts more effectively.

This paper aims to develop a customer profiling system using image processing to suggest a stock management strategy for an apparel store. LabVIEW was used as the platform for the implementation of the customer profiling system. The Vision Builder for Automated Inspection (VBAI), an image processing toolbox of LabVIEW, was used to implement the image processing. The system that was developed operates offline. For this study, the experimental and reliability tests were done in a controlled environment. Two parameters were put into consideration – the gender identification and the shirt size classification. One hundred test subjects participated in this study, having forty females and sixty males. Considering the said parameters independently, the gender identification, and the shirt size classification have demonstrated a system reliability of 94% and 95% respectively. The results showed that the system worked at a system reliability of 94% for both gender identification and shirt size classification.

Abstract Format






Accession Number


Shelf Location

Archives, The Learning Commons, 12F, Henry Sy Sr. Hall

Physical Description

179 leaves :illustrations (some colored) ; 28 cm.

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