Feature Selection Based on Minimum Overlap Probability (MOP) in Identifying Beef and Pork
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2016, Vol 7, Issue 3
Abstract
Feature selection is one of the most important techniques in image processing for classifying. In classifying beef and pork based on texture feature, feature overlaps are difficult issues. This paper proposed feature selection method by Minimum Overlap Probability (MOP) to get the best feature. The method was tested on two datasets of features of digital images of beef and pork which had similar textures and overlapping features. The selected features were used for data training and testing by Backpropagation Neural Network (BPNN). Data training process used single features and several selected feature combinations. The test result showed that BPNN managed to detect beef or pork images with 97.75% performance. From performance a conclusion was drawn that MOP method could be used to select the best features in feature selection for classifying/identifying two digital image objects with similar textures.
Authors and Affiliations
Khoerul Anwar, Agus Harjoko, Suharto Suharto
Keywords
Related Articles
- EP ID EP138565
- DOI 10.14569/IJACSA.2016.070345
- Views 112
- Downloads 0
Embedded Feature Selection Method for a Network-Level Behavioural Analysis Detection Model
Feature selection in network-level behavioural analysis studies is used to represent the network datasets of a monitored space. However, recent studies have shown that current behavioural analysis methods at the network-...
Using FDD for Small Project: An Empirical Case Study
Empirical analysis evaluates the proposed system via practical experience and reveals its pros and cons. Such type of evaluation is one of the widely used validation approach in software engineering. Conventional softwar...
A Hybrid Genetic Algorithm with Tabu Search for Optimization of the Traveling Thief Problem
Until now, several approaches such as evolutionary computing and heuristic methods have been presented to optimize the traveling thief problem (TTP). However, most of these approaches consider the TTP components independ...
A Comparative Study of the Decisional Needs Engineering Approaches
Requirements Engineering (RE) is an important phase in a project of systems development. It helps design-analysts to design and to model the expression of the end-user needs, and their expectations vis-a-vis their future...
Rating Prediction with Topic Gradient Descent Method for Matrix Factorization in Recommendation
In many online review sites or social media, the users are encouraged to assign a numeric rating and write a textual review as feedback to each product that they have bought. Based on users’ history of feedbacks, recomme...