SIFT ve Şablon Eşleme ile Lastik İzi Desenlerinin Tanınması

Year 2022, , 634 - 643, 31.05.2022

Asuman Günay Yılmaz , Nasif Nabiyev

https://doi.org/10.31202/ecjse.990247

Abstract

Lastik izi desenlerinin tanınması hem suç olay mahallerinin araştırılmasında hem de trafik kazalarında kazaya karışan araçların belirlenmesinde önemli role sahiptir. Taşıdığı zengin doku bilgisi nedeniyle lastiklerden alınan desen görüntülerinin tanınmasında doku öznitelikleri kullanılmaktadır. Fakat olay yerlerinden alınan lastik izlerinin tanınması konusu yeterince çalışılmamıştır. Bu çalışmada lastik izi/iz parçası görüntülerinin tanınması amacıyla SIFT tabanlı öznitelikler ve şablon eşleme yöntemleri kullanılmıştır. Deneylerde temiz izlerden alınan kesitlerin kirli izlerin ve kirli izlerden alınan kesitlerin, temiz izlerle eşleştirilmesi işleminde state of art yöntemlere göre daha yüksek tanıma başarımı elde edilmiştir.

Keywords

Lastik izi görüntüsü, SIFT, şablon eşleme

Recognition of Tire Track Patterns Using SIFT and Template Matching

Abstract

Recognition of tire track patterns has an important role in both the investigation of crime scenes and the identification of vehicles involved in traffic accidents. Due to the rich texture information they have, texture features are generally used to recognize track images taken from tires. However, recognition of tire tracks taken from crime scenes has not been studied sufficiently. In this study, SIFT-based features and template matching methods were used to recognize tire track/tire track fragment images. In the experiments, fragments taken from clean tracks and fragments taken from dirty tracks were matched with clean track images, and higher recognition performance was achieved compared to state of art methods.

Keywords

Tire track image, SIFT, template matching

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