• Structural Engineering and Mechanics
• /
• v.53 no.1
• /
• pp.147-158
• /
• 2015

Elements used in steel structures may be considered as an assembly of number of thin flat walls. Local buckling of these members can limit the buckling capacity of axial load resistance or flexural strength. We can avoid a premature failure, caused by effects of local buckling, by limiting the value of the wall slenderness which depend on its critical buckling stress. According to Eurocode 3, the buckling stress is calculated for an internal wall assuming that the latter is a simply supported plate on its contour. This assumption considers, without further requirement, that the two orthogonal walls to this wall are sufficiently rigid to constitute fixed supports to it. In this paper, we focus on webs of steel profiles that are internal walls delimited by flanges profiles. The objective is to determine, for a given web, flanges dimensions from which the latter can be considered as simple support for this web.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.77.4-77
• /
• 2001

The quality of agricultural products is classified with various factors which are measured and determined by destructive and/or nondestructive method. NIR spectrum analysis method is used to determine internal qualities such as a brix and an acidity. CCD color camera is used to measure external quality like color and a size of fruit. today, nondestructive methods are widely researched. The quality and the garde of fruit loaded into a cup automatically and measured in real time by camera and NIR system is determined by internal and external factors. This paper proposes modified boundary tracking algorithm which detects the contour of fruit´s color image and make chain code faster than conventional method ...

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.10
• /
• pp.3708-3728
• /
• 2021

Indian herbal plants are used in agriculture and in the food, cosmetics, and pharmaceutical industries. Laboratory-based tests are routinely used to identify and classify similar herb species by analyzing their internal cell structures. In this paper, we have applied computer vision techniques to do the same. The original leaf image was preprocessed using the Chan-Vese active contour segmentation algorithm to efface the background from the image by setting the contraction bias as (v) -1 and smoothing factor (µ) as 0.5, and bringing the initial contour close to the image boundary. Thereafter the segmented grayscale image was fed to a leaky capacitance fired neuron model (LCFN), which differentiates between similar herbs by combining different groups of pixels in the leaf image. The LFCN's decay constant (f), decay constant (g) and threshold (h) parameters were empirically assigned as 0.7, 0.6 and h=18 to generate the 1D feature vector. The LCFN time sequence identified the internal leaf structure at different iterations. Our proposed framework was tested against newly collected herbal species of natural images, geometrically variant images in terms of size, orientation and position. The 1D sequence and shape features of aloe, betel, Indian borage, bittergourd, grape, insulin herb, guava, mango, nilavembu, nithiyakalyani, sweet basil and pomegranate were fed into the 5-fold Bayesian regularization neural network (BRNN), K-nearest neighbors (KNN), support vector machine (SVM), and ensemble classifier to obtain the highest classification accuracy of 91.19%.

• Imaging Science in Dentistry
• /
• v.51 no.1
• /
• pp.81-86
• /
• 2021

Purpose: This study was performed to assess and describe the imaging features of 40 cases of Stafne bone defects (SBDs) on computed tomographic (CT) examinations. Materials and Methods: This study collected data, including age and sex, from 40 patients with SBDs who underwent CT exams. The imaging features of the SBDs were assessed in terms of their location, average size, the relationship of their contour with the cortical plate of the lingual mandible, bone margins, degree of internal density, shape, topographic relationship between the defect and the mandibular edge, the distance from the SBD to the base of the mandible, and the Ariji classification (type I, II, and III). Results: The average age was 57.3 years(range, 28-78 years), and the patients were predominantly male (70%). In all cases (100%), the posterior unilateral lingual SBD variant was observed. Within the Ariji classification, type I was the most common (60%). Among the most frequently observed radiographic characteristics were thick sclerotic bone margin across the entire defect contour, completely hypointense internal content, an oval shape, and continuity with the mandibular base with discontinuity of the mandibular edge. Conclusion: This study showed that posterior SBDs could present with an oval or rounded shape, complete hypodensity, and thick sclerotic margins. Likewise, SBDs could appear almost anywhere, with minor differences from the classic SBD appearance. It is fundamental for dental practitioners to know the imaging features of SBDs, since they are diagnosed primarily based on imaging.

• The KIPS Transactions:PartB
• /
• v.16B no.4
• /
• pp.289-298
• /
• 2009

Active Contour Model, that is, Snake algorithm is effective for detection and tracking the objects. However, this algorithm has some drawbacks; numerous parameters must be designed(weighting factors, iteration steps, etc.), a reasonable initialization must be available and moreover suffers from numerical instability. Therefore we propose a novel Energy Corrected Snake(ECS) algorithm which improved on external energy of Snake algorithm for detection and tracking the moving object more effectively. The proposed algorithm uses the difference image, getting when the object is moving. It copies four direction images from the difference image and performs the accumulating compute to erasing image noise, so that it gets external energy steadily. Then external energy united with contour that is computed by internal energy. Consequently we can detect and track the moving object more speedily and easily. To show the effectiveness of the proposed algorithm, we experiment on 3 situations. The experimental results showed that the proposed algorithm outperformed by 6$\sim$9% of detection rate and 6$\sim$11% of tracker detection rate compared with the Snake algorithm.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.1
• /
• pp.54-66
• /
• 1997

Efficient retrieval of image data is an important research issue in multimedia database. This paper proposes a new approach to a content-based image retrieval which allows queries to be composed of the local texture patterns and the slope components of contour points. The texture patterns extracted from the source image using the graylevel co-occurrence matrix and the slope components of contour points extracted from the binary image are converted into a internal feature representation of reduced dimensionality which preserves the perceptual similarity and those features can be used in creating efficient indexing structures for a content-based image retrieval. Experimental results of the image retrievalare presented to illustrate the usefulness of this approach that demonstrates the precision 82%, the recall 87% and the average rang 3.3 in content-based image data retrieval.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.5
• /
• pp.2363-2374
• /
• 2016

Communication occurs through verbal elements, which usually involve language, as well as non-verbal elements such as facial expressions, eye contact, and gestures. In particular, among these non-verbal elements, gestures are symbolic representations of physical, vocal, and emotional behaviors. This means that gestures can be signals toward a target or expressions of internal psychological processes, rather than simply movements of the body or hands. Moreover, gestures with such properties have been the focus of much research for a new interface in the NUI/NUX field. In this paper, we propose a method for recognizing the number of fingers and detecting the hand region based on the depth information and geometric features of the hand for application to an NUI/NUX. The hand region is detected by using depth information provided by the Kinect system, and the number of fingers is identified by comparing the distance between the contour and the center of the hand region. The contour is detected using the Suzuki85 algorithm, and the number of fingers is calculated by detecting the finger tips in a location at the maximum distance to compare the distances between three consecutive dots in the contour and the center point of the hand. The average recognition rate for the number of fingers is 98.6%, and the execution time is 0.065 ms for the algorithm used in the proposed method. Although this method is fast and its complexity is low, it shows a higher recognition rate and faster recognition speed than other methods. As an application example of the proposed method, this paper explains a Secret Door that recognizes a password by recognizing the number of fingers held up by a user.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.2
• /
• pp.670-675
• /
• 2015

Medical imaging is one of the most powerful tools for gaining information about internal organs and tissues. It is a challenging task to develop sophisticated image analysis methods in order to improve the accuracy of diagnosis. The objective of this paper is to develop a Computer Aided Diagnostics (CAD) scheme for Brain Tumour detection from Magnetic Resonance Image (MRI) using active contour models and to investigate with several approaches for improving CAD performances. The problem in clinical medicine is the automatic detection of brain Tumours with maximum accuracy and in less time. This work involves the following steps: i) Segmentation performed by Fuzzy Clustering with Level Set Method (FCMLSM) and performance is compared with snake models based on Balloon force and Gradient Vector Force (GVF), Distance Regularized Level Set Method (DRLSE). ii) Feature extraction done by Shape and Texture based features. iii) Brain Tumour detection performed by various tree classifiers. Based on investigation FCMLSM is well suited segmentation method and Random Forest is the most optimum classifier for this problem. This method gives accuracy of 97% and with minimum classification error. The time taken to detect Tumour is approximately 2 mins for an examination (30 slices).

• Aerospace Engineering and Technology
• /
• v.12 no.1
• /
• pp.207-212
• /
• 2013

To investigate the possibility of using artificial means for the control of shear layers in swirl jets, a shear excitation device is introduced. The device consists of co-centric dual nozzles with internal lobes (i.e., convex surfaces) of small height to induce disturbance. The number of convexities can be varied to produce the various modes in azimuthal direction. The acquired velocity data of the swirling jets, with and without the lobes, are numerically simulated in 2-D contour plots and 3-D particle trace plots. The results are compared with the baseline (i.e., no excitation case) at various excitation modes. Conclusively it is observed that the artificial excitation method is effective in the control of the vortical structure in swirling jets.

• Tuberculosis and Respiratory Diseases
• /
• v.61 no.2
• /
• pp.157-161
• /
• 2006

A 70-year-old man was referred to the department of pulmonology due to blood tinged sputum and an abnormal chest X-ray. The chest X-ray and CT scans revealed a lobulated contour mass-like lesion in the left upper lung field. The bronchoscopic examination showed a whitish and polypoid mass occluding the left upper lobe bronchus. A biopsy specimen from the lesion revealed many aspergillus hyphae. Intravenous and oral itraconozole were administered over a 4 weeks period. Several months later, the size of the mass on chest X-ray increased and a percutaneous lung biopsy revealed a sarcomatoid carcinoma. We reported a case of lung cancer that was obscured by an endobronchial aspergilloma with a review of the relevant literature.