Baggage Detection and Recognition Using Local Tri-Directional Pattern - Ayesha; Ali Khan; Muhammad Nadeem; Syeda Wajiha Zahra; Ali Arshad; Saman Riaz; Usman Shahid (International Journal of Mobile Computing Technology, 2023)
Nowadays, pattern-based image retrieval algorithms are gaining popularity just because of their uniqueness. There are several issues in the previously proposed systems. The proposed system resolves issues highlighted in the literature. Our proposed system is tested on two image datasets ILIDS and PETS 2006. LTDP provides good results as compared to LBP in baggage detection on two classes that either bag is present or not in an image because LTDP works on finding the difference between adjacent neighbors and magnitude pattern which is either 0 or 1 which means either bag is present or not. In addition to LTDP patterns, HOG transformation has also been used for better feature extraction results. The results obtained through ANN are 90% whereas SVM depicts 50% accuracy; and through classification learner, 75% accuracy is obtained.
Keywords: LBP; LTDP; baggage detection; pattern-based image retrieval algorithms