What's in my closet?: Image classification using fuzzy logic

TL;DR

This paper presents a fuzzy logic-based image classification system in MATLAB that identifies clothing items such as dresses, shirts, and pants from input images using Mamdani inference and characteristic functions.

Contribution

It introduces a novel fuzzy inference approach for clothing image classification, combining image processing with Mamdani systems for pattern recognition.

Findings

Effective identification of clothing types from images

Utilization of Mamdani fuzzy inference for pattern recognition

Demonstrated system accuracy with multiple input images

Abstract

A fuzzy system was created in MATLAB to identify an item of clothing as a dress, shirt, or pair of pants from a series of input images. The system was initialized using a high-contrast vector-image of each item of clothing as the state closest to a direct solution. Nine other user-input images (three of each item) were also used to determine the characteristic function of each item and recognize each pattern. Mamdani inference systems were used for edge location and identification of characteristic regions of interest for each item of clothing. Based on these non-dimensional trends, a second Mamdani fuzzy inference system was used to characterize each image as containing a shirt, a dress, or a pair of pants. An outline of the fuzzy inference system and image processing techniques used for creating an image pattern recognition system are discussed.