Threshold Based Indexing of Commercial Shoe Print to Create Reference and Recovery Images

TL;DR

This paper presents a method for processing and indexing shoe print images using threshold-based segmentation and image enhancement techniques to facilitate efficient search and retrieval in forensic databases.

Contribution

The paper introduces a novel threshold-based indexing approach for shoe print images, combining image enhancement, restoration, and segmentation for forensic database search.

Findings

Effective segmentation of shoe prints using global threshold

Improved image quality through histogram-based enhancement

Validated method with simulation results

Abstract

One of the important evidence in a crime scene that is normally overlooked but very important evidence is shoe print as the criminal is normally unaware of the mask for this. In this paper we use image processing technique to process reference shoe images to make it index-able for a search from the database the shoe print impressions available in the commercial market. This is achieved first by converting the commercially available image through the process of converting them to gray scale then apply image enhancement and restoration techniques and finally do image segmentation to store the segmented parameter as index in the database storage. We use histogram method for image enhancement, inverse filtering for image restoration and threshold method for indexing. We use global threshold as index of the shoe print. The paper describes this method and simulation results are included to validate the method.