MSER-Vertical Sobel for Vehicle Logo Detection
Dublin Core
Title
MSER-Vertical Sobel for Vehicle Logo Detection
Subject
car logo detection; maximally stable extremal region; vertical sobel
Description
Detecting a vehicle logo is the first step before the actual recognition of the logo. However, detecting logos can pose difficulties
due to various factors, including logo variations, differing scales and orientations, background interference, varying lighting
conditions, and partial obstruction. This paper presents a vehicle logo detection method using handcrafted features. We used
a combination of Maximally Stable Extremal Region (MSER) and Vertical Sobel. We combine vertical Sobel with MSER to
overcome MSER's limitation in recognizing objects of different sizes. These two features are merged using closing morphology
operation to form blobs selected as logo candidate areas. Moreover, a Support Vector Machine (SVM) is implemented to
choose a logo area by analyzing each candidate's Histogram of Oriented Gradient (HOG). The proposed method was compared
to other methods by implementing them on the same dataset. The significant advantage of using MSER-Vertical Sobel is its fast
computation time. It is faster than other approaches that use non-handcrafted features. The test results show that the MSERVertical Sobel can achieve high accuracy and the fastest computation time.
due to various factors, including logo variations, differing scales and orientations, background interference, varying lighting
conditions, and partial obstruction. This paper presents a vehicle logo detection method using handcrafted features. We used
a combination of Maximally Stable Extremal Region (MSER) and Vertical Sobel. We combine vertical Sobel with MSER to
overcome MSER's limitation in recognizing objects of different sizes. These two features are merged using closing morphology
operation to form blobs selected as logo candidate areas. Moreover, a Support Vector Machine (SVM) is implemented to
choose a logo area by analyzing each candidate's Histogram of Oriented Gradient (HOG). The proposed method was compared
to other methods by implementing them on the same dataset. The significant advantage of using MSER-Vertical Sobel is its fast
computation time. It is faster than other approaches that use non-handcrafted features. The test results show that the MSERVertical Sobel can achieve high accuracy and the fastest computation time.
Creator
Gamma Kosala, Agus Harjoko, Sri Hartati
Source
http://jurnal.iaii.or.id
Publisher
Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association
Date
October 2023
Contributor
Sri Wahyuni
Rights
ISSN Media Electronic: 2580-0760
Format
PDF
Language
English
Type
Text
Files
Collection
Citation
Gamma Kosala, Agus Harjoko, Sri Hartati, “MSER-Vertical Sobel for Vehicle Logo Detection,” Repository Horizon University Indonesia, accessed February 3, 2026, https://repository.horizon.ac.id/items/show/10080.