title: Content-based image retrieval system for solid waste bin level detection and performance evaluation.
abstract: This paper presents a CBIR system to investigate the use of image retrieval with an extracted texture from the image of a bin to detect the bin level. Various similarity distances like Euclidean, Bhattacharyya, Chi-squared, Cosine, and EMD are used with the CBIR system for calculating and comparing the distance between a query image and the images in a database to obtain the highest performance. In this study, the performance metrics is based on two quantitative evaluation criteria. The first one is the average retrieval rate based on the precision-recall graph and the second is the use of F1 measure which is the weighted harmonic mean of precision and recall. In case of feature extraction, texture is used as an image feature for bin level detection system. Various experiments are conducted with different features extraction techniques like Gabor wavelet filter, gray level co-occurrence matrix (GLCM), and gray level aura matrix (GLAM) to identify the level of the bin and its surrounding area. Intensive tests are conducted among 250 bin images to assess the accuracy of the proposed feature extraction techniques. The average retrieval rate is used to evaluate the performance of the retrieval system. The result shows that, the EMD distance achieved high accuracy and provides better performance than the other distances.
authors: Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia, Bangi, Selangor DE, Malaysia. Electronic address: hannan@ukm.edu.my.
authors: M A
authors: MA
authors: Hannan
authors: Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia, Bangi, Selangor DE, Malaysia. Electronic address: maher@eng.ukm.my.
authors: M
authors: M
authors: Arebey
authors: Institute of Climate Change, Universiti Kebangsaan Malaysia, Bangi, Selangor DE, Malaysia. Electronic address: rawshan@ukm.edu.my.
authors: R A
authors: RA
authors: Begum
authors: Department of Civil and Structural Engineering, Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia, Bangi, Selangor DE, Malaysia. Electronic address: drhb@ukm.edu.my.
authors: Hassan
authors: H
authors: Basri
authors: Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia, Bangi, Selangor DE, Malaysia. Electronic address: md.abdulla@siswa.ukm.edu.my.
authors: Md Abdulla
authors: MA
authors: Al Mamun
mesh_terms: D000465:Algorithms; D007091:Image Processing, Computer-Assisted; D012037:Refuse Disposal / Q000295:instrumentation; D062611:Solid Waste / Q000032:analysis*; D018505:Waste Management / Q000295:instrumentation* / Q000379:methods*
chemical_list: D062611:Solid Waste
keywords: CBIR; Feature extraction; GLAM; GLCM; Gabor; Solid waste bin level