پردازش تصویر

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1 - Improving Age Estimation of Dental Panoramic Images Based on Image Contrast Correction by Spatial Entropy Method
Masoume Mohseni Hussain Montazery Kordy Mehdi Ezoji
20.1001.1.16823745.1400.19.2.13.2

In forensic dentistry, age is estimated using dental radiographs. Our goal is to automate these steps using image processing and pattern recognition techniques. With a dental radiograph, the contour is extracted and features such as apex, width and tooth length are dete More

In forensic dentistry, age is estimated using dental radiographs. Our goal is to automate these steps using image processing and pattern recognition techniques. With a dental radiograph, the contour is extracted and features such as apex, width and tooth length are determined, which are used to estimate age. Optimizing the resolution of radiographic images is an important step in contour extraction and age estimation. In this article, the aim is to improve the image resolution in order to extract the appropriate area and proper segmentation of the tooth, which makes it possible to estimate age better. In this model, due to the low resolution of radiographic images, in order to increase the accuracy of extracting the desired area of each tooth (ROI), the image resolution increases using spatial entropy based on the spatial distribution of pixel brightness, along with another increasing resolution method, like the Laplacian pyramids. Increasing the resolution of the image leads to the extraction of appropriate ROI and the removal of unwanted areas. The database used in this study is 154 adolescent panoramic radiographs, of which 73 are male and 81 are female. This database is prepared from Babol University of Medical Sciences. The results show that by using fixed tooth segmentation methods and only by applying the proposed effective method to improve image resolution, the extraction of appropriate ROI increased from 66% to 78% which shows a good improvement. The extracted ROI is then delivered to the segmented block and the contour extracted. After contour extraction, age is estimated. The age estimation using the proposed method is closer to the manual age estimate compared to the method that does not use the proposed algorithm to increase the image resolution. Manuscript profile
Open Access Article
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2 - An Intelligent Vision System for Automatic Forest Fire Surveillance
Mohammad Sadegh Kayhanpanah Behrooz Koohestani
20.1001.1.16823745.1401.20.1.3.7

Fighting forest fires to avoid their potential dangers as well as protect natural resources is a challenge for researchers. The goal of this research is to identify the features of fire and smoke from the unmanned aerial vehicle (UAV) visual images for classification, o More

Fighting forest fires to avoid their potential dangers as well as protect natural resources is a challenge for researchers. The goal of this research is to identify the features of fire and smoke from the unmanned aerial vehicle (UAV) visual images for classification, object detection, and image segmentation. Because forests are highly complex and nonstructured environments, the use of the vision system is still having problems such as the analogues of flame characteristics to sunlight, plants, and animals, or the smoke blocking the images of the fire, which causes false alarms. The proposed method in this research is the use of convolutional neural networks (CNNs) as a deep learning method that can automatically extract or generate features in different layers. First, we collect data and increase them according to data augmentation methods, and then, the use of a 12-layer network for classification as well as transfer learning method for segmentation of images is proposed. The results show that the data augmentation method used due to resizing and processing the input images to the network to prevent the drastic reduction of the features in the original images and also the CNNs used can extract the fire and smoke features in the images well and finally detect and localize them. Manuscript profile

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List of Articles پردازش تصویر