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Öğe Centre of mass model - A novel approach to background modelling for segmentation of moving objects(Elsevier, 2007) Oral, Mustafa; Deniz, UmutThis paper describes a novel method, centre of mass model, to detect moving objects in a dynamic scene based on background subtraction. Any displacement of the position of centre of mass (CoMs) in two consecutive frames is the indicator of a moving object in a scene. Dividing a scene into subregions and modelling them as individual masses allow segmentation of the moving object(s). In the proposed scheme, an image is divided into blocks that are called super-pixels and each super-pixel is represented with the x and y components of CoM of a block. The segmentation is achieved by taking the absolute difference between CoM of current super-pixel and the mean of CoMs of previous corresponding super-pixels, and thresholding the difference with a dynamically updated value. A comparative work has been carried out to evaluate the performance of the proposed model and the previously reported seven different methods. The model produced consistent outputs for the images taken in different environmental conditions. The moving objects were successfully segmented with no post-processing operations. Centre of mass model demonstrated better overall performance than the methods previously reported. Its output was superior for auto-focused video images. (c) 2007 Published by Elsevier B.V.Öğe The evaluation of gnathiid (Crustacea: Isopoda: Gnathidae) parasitism in goldblotch grouper (Epinephelus costae Staindahner, 1878) in the northeastern Mediterranean Sea using the self-organizing map (SOM)(Springer, 2011) Genc, Ercument; Oral, Mustafa; Erol, CavitThe self-organizing map (SOM), which is widely used in economics and engineering applications, is a type of artificial neural network trained without supervision. SOM is used to represent multidimensional data in much lower dimensional spaces-usually in two dimensions (2D)-while preserving the topological properties of the input space. In this study, 2D maps were produced by using SOM to display the relationship between seasons, length, weight, and isopod infestation of goldblotch grouper (Epinephelus costae Staindahner, 1878). This is first study of gnathiid isopod praniza larvae infesting goldblotch grouper (E. costae Staindahner, 1878) in the northeast Mediterranean Sea (36A degrees 36' N-36A degrees 07' E, 35A degrees 52' N-36A degrees 25' E) in Iskenderun Bay. Fish were sampled monthly from Iskenderun Bay for a period of 12 months from 2006 May to 2007 April (Nt = 331, Wt +/- SD (range) = 392.92 +/- 72.76g (169 - 927g), TLt +/- SD(range) = 30.85 +/- 3.88 cm (17 - 48.3 cm). Gnathia sp. was only extracted from the epithelium of the buccal cavity and internal side of the gills arch. The monthly patterns in infested fish samples (Np = 109, Wp +/- SD (range) - 349.25 +/- 182.79g (169 - 853g), TLt +/- SD(range) - 26.05 +/- 12.68cm (18.2 - 45.0cm)) infestation rates (mean prevalence, P = 28.12% (0-60) and mean intensity (MI +/- SD - 23.69 +/- 14.78(4 - 82), the relationship between length-weight and infested/non-infested fish were calculated. Although the gnathiid parasite high intensities were observed in fish, there was no significant effect on the growth and general health condition of infested fish.Öğe İskenderun Körfezi’nde yaşayan orfoz balığı (Ephinephelus marginatus Lowe 1834)’ ndaki parazitlenmenin öz örgütlenmeli haritalarla yeniden değerlendrilmesi(2008) Oral, Mustafa; Genç, ErcümentMühendislik ve ekonomik problemlerin çözümünde sıklıkla kullanılan Yapay Sinir Ağları (YSA)'nın bir alt kolu olan Öz Örgütlenmeli Haritalar (ÖÖH) yöntemi; çok parametreli durumları iki boyutlu (2D) haritalara indirgeyerek, duruma etki eden parametrelerin birbirleri ile olan ilişkilerini görsel olarak sunmaktadır. Bu çalışma; daha önce İskenderun Körfezi'nden elde edilen Orfoz (Ephinephelus marginatus)'ların; mevsimsel olarak boy, ağırlık ve parazitlenme (Nematod, Cestod, İsopod) ilişkilerinin; ÖÖH kullanılarak (2D haritalara indirgenmesi), yeniden değerlendirilmesine dayanmaktadırÖğe Morphometric and meristic variation between stocks of Bluefish (Pomatomus saltatrix) in the Black, Marmara, Aegean and northeastern Mediterranean Seas(Elsevier, 2006) Turan, Cemal; Oral, Mustafa; Ozturk, Bayram; Duzgunes, ErtugThe genetic and morphological variation of Pomatomus saltatrix were studied based on morphometric and meristic analyses of samples collected throughout the Black Seas, Marmara, Aegean and eastern Mediterranean Seas. In discriminant function analysis, plotting first and second discriminant functions explained 61 and 77% of the between-group variation for morphometric and meristic analyses, respectively, and indicated existence of three morphologically differentiated groups of P saltatrix. Consistent differences in the summer and winter samples of the eastern Black Sea, the adjacent sea populations of western Black Sea, Marmara Sea and Aegean Sea, which were overlapping and northeastern Mediterranean samples were observed. The detected pattern of morphological differentiation also reflects their geographic isolation. The overall random assignment of individuals into their original population was moderate for morphometric (54%) and meristic (64%) characters. Both for morphometric and meristic analysis, the highest reclassification rate was observed for the eastern Black Sea and northeastem Mediterranean Sea samples, the most clearly isolated groups. Examination of the contribution of each morphometric and meristic character to the first and second discriminant functions revealed that the observed differences were mainly from head measurements, body depth, lateral scale and vertebrate numbers, indicating these characters to be important in the description of population characteristics. Mantel's test showed that the Mahalanobis distance between the populations both for morphometric (r = -0.282; P = 0.226) and meristic (r = 0.632; P = 0.119) were not significantly associated with their geographical distances. (c) 2006 Elsevier B.V. All rights reserved.Öğe Motion detection in moving pictures(2005) Oral, Mustafa; Deniz, UmutMotion analysis is one of the major techniques which is used in applications related with interpretation, processing and compressing digital images. In this thesis, seven different methods that are widely used for the motion detection in a moving picture sequence, were studied and implemented, and their performances were discussed. These methods were investigated under two major headings namely Background Subtraction Methods and Statistical Methods. The performance tests for the methods were carried out for the images that were taken under various illumination conditions. The results showed that the background subtraction methods are very sensitive to sudden illumination changes on a running sequence which is a major drawback. While both of the methods are quite satisfactory for indoor scenes that provide stable illumination conditions, the methods that were studied under secondary group of the statistical methods have been found to be successful for the outdoor scenes that present sudden illumination changes. Although, the pitfalls of the methods resulting sudden illumination changes have been improved, the need for taking the images under a carefully illuminated environment, needs further investigation. © 2005 IEEE.Öğe A novel approach for motion segmentation in moving pictures: Centre of Mass Model(Ieee, 2007) Oral, Mustafa; Deniz, UmutA novel background model for segmentation of moving objects in running images is presented in this paper. The segmentation algorithm is based on the statistics of the current and previous locations of center of mass of super pixels that are the collection of a group of pixels. The algorithm is superior to those previously reported in the literature due to its immunity to sudden illumination changes and slight changes in the intensity distribution functions of the super-pixels. The performance of the Center of Mass Model is compared with previously reported seven different models that were selected from the Background Subtracting Methods and the Statistical Methods.
