The increasing demand for the use of solar energy as an alternative source of energy to generate electricity has multiplied the need for more photovoltaic (PG) arrays. With the growth of the PV manufacturing industry,...
详细信息
ISBN:
(纸本)9781509025978
The increasing demand for the use of solar energy as an alternative source of energy to generate electricity has multiplied the need for more photovoltaic (PG) arrays. With the growth of the PV manufacturing industry, automation for defect detection is seen as a great potential in ensuring the quality of these PV modules. Hotspot formation due to defects is detrimental to the performance of PV devices. Thus this research aims to detect and isolate hotspot areas in PV modules by applying two machine learning techniques, namely Korean color quantization for pre-processing, and density based spatial clustering of applications with noise (DBSCAN) for processing, in the images captured by an infrared camera. In the preprocessing. K-means clustering algorithm produced a quantized color image represented by the contours while in the processing or clustering part, DBSCAN resulted in the segmentation of the image, isolating the hotspot. Further investigation of the PV module through visual inspection found a crack in one of the solar cell where the hotspot occurred.
In the area of robotic vision we are interested in developing algorithms for the control of a robot manipulator by means of visual feedback. image analysis and exploitation of the image features are therefore steps of...
详细信息
ISBN:
(纸本)0780332598
In the area of robotic vision we are interested in developing algorithms for the control of a robot manipulator by means of visual feedback. image analysis and exploitation of the image features are therefore steps of importance. This paper deals with the problem of three-dimensional localization of objects representing circular patterns. The first part of the paper is concerned with the parametrization of elliptic curves and a second part is dedicated to the estimation of an object's position and orientation.
In this paper, we present a study on automatic detection of center coordinate and radius of femoral heads in coronal MR slices belong to the patients with Legg-Calve-Perthes (LCP) disease. LCP which lead to dysfunctio...
详细信息
ISBN:
(纸本)9781538615010
In this paper, we present a study on automatic detection of center coordinate and radius of femoral heads in coronal MR slices belong to the patients with Legg-Calve-Perthes (LCP) disease. LCP which lead to dysfunction caused by the deformity of the spherical structure of the femoral head in hip joint is a hip disorder in pediatric orthopaedics. Especially in segmentation studies, automatic detection of femoral head is an important issue in the assessment and quantification studies of the hip diseases. So that, we aimed to detect the healthy and pathological femoral heads in MR slices of LCP patients by using the Circular Hough Transform (CHT) in this study. In this context, first the MR sections are divided vertically into two equal halves to separate the hip joints and then edge images are obtained by using Canny's edge detection method. Finally, femoral heads are detected by performing the CHT on edge images. Successful results were achieved in experiments on healthy and pathological hip joints in 24 coronal MR images belong to 13 patients and the observed outputs were compared.
In this paper we describe integrated multimedia processing for Video Scout, a system that segments and indexes TV programs according to their audio, visual, and transcript information Video Scout represents a future d...
详细信息
ISBN:
(纸本)0780367251
In this paper we describe integrated multimedia processing for Video Scout, a system that segments and indexes TV programs according to their audio, visual, and transcript information Video Scout represents a future direction for personal video recorders In addition to using electronic program guide metadata and a user profile, Scout allows the users to request specific topics within a program For example, users can request the video clip of the President speaking from a half-hour news program Video Scout has three modules (i) Video Pre-processing, (ii) Segmentation and Indexing, and (iii) Storage and User Interface Segmentation and Indexing, the core of the system, incorporates a Bayesian framework that integrates information from the audio, visual, and transcript (closed captions) domains This framework uses three layers to process low, mid, and high-level multimedia information The high-level layer generates semantic information about TV program topics This paper describes the elements of the system and presents results from running Video Scout on real TV programs.
images are the easiest medium through which people can express their emotions on social networking sites. Social media users are increasingly using images and videos to express their opinions and share their experienc...
详细信息
ISBN:
(纸本)9781467377584
images are the easiest medium through which people can express their emotions on social networking sites. Social media users are increasingly using images and videos to express their opinions and share their experiences. Sentiment analysis of such large scale visual content can help better extract user sentiments toward events or topics, such as those in image tweets, so that prediction of sentiment from visual content is complementary to textual sentiment analysis. Significant progress has been made with this technology, however, there is little research focus on the picture sentiments. In this work, an image sentiment prediction framework is built with Convolutional Neural Networks (CNN). Specifically, this framework is pretrained on a large scale data for object recognition to further perform transfer learning. Extensive experiments were conducted on manually labeled Flickr image dataset. To make use of such labeled data, we employ a progressive strategy of domain specific fine tuning of the deep network. The results show that the proposed CNN training can achieve better performance in image sentiment analysis than competing networks.
In the last few years, with increasing popularity of the visualcommunications technology, also the interest in robbing the secret information has risen. The field of information security has an important issue even i...
详细信息
ISBN:
(纸本)9781479934485
In the last few years, with increasing popularity of the visualcommunications technology, also the interest in robbing the secret information has risen. The field of information security has an important issue even in the field of medical imagery. visual Cryptography (VC) is a revolutionary encryption methodology to share the image secret information in a secure way. This paper considers the problem of encoding a secret gray scale image GI into n shares of meaningful halftone images within the scheme of visual cryptography. We provide an overview of the emerging visual Cryptography (VC) techniques used in the secure transfer of the thousands of images collected and stored in medical imagery system. In this paper, we propose a (2,2) improved gray scale visual secret sharing (IGVSS) scheme using dynamic threshold method to reduce the problems of computational complexity and pixel expansion. The proposed IGVSS scheme, to encode the secret information into meaningful shares for producing high quality share images. For encoding the secret information, VC is demonstrated in two levels. In first level, single Meaningful visualimage (MVI) is used to generate multiple shares. In second level, two meaningful visualimages are employed to generate multiple shares. It is hard to perceive any clues about a secret image from individual shares. The experimental result ensures the security and quality of the reconstructed secret images.
The paper is dedicated to the problem of the quality assurance of foodstuff and particularly bacteria detection in liquid exudes. It demonstates disadvantages of the existing methods and suggests a new method based on...
详细信息
ISBN:
(纸本)9781479923854
The paper is dedicated to the problem of the quality assurance of foodstuff and particularly bacteria detection in liquid exudes. It demonstates disadvantages of the existing methods and suggests a new method based on the imageprocessing and machine learning techniques. The principal component analysis shows that this problem is quite hard for existing algorithms. Also the usage of a few classifiers is considered and the evaluation of their effectiveness is shown.
The segmentation process is one of the most important steps in image analysis since its performance directly affects the subsequent steps in imageprocessing. In this paper we investigated Conic Section Function Neura...
详细信息
The accurate detection of region(s)-of-interest (ROI) via Active Contour Method (ACM) is a well-known and evolving research topic in image segmentation. A novel region-based active contour method is proposed that can ...
详细信息
ISBN:
(纸本)9781538631423
The accurate detection of region(s)-of-interest (ROI) via Active Contour Method (ACM) is a well-known and evolving research topic in image segmentation. A novel region-based active contour method is proposed that can segment real and synthetic images with blurred borders more efficiently. Additionally, a new Signed Pressure Force (SPF) function named as Hyperbolic Trigonometric Signed Pressure Force Function (HTSPF) is introduced, that is able to detect the contour of ROI of diverse intensities, even at weak and blurred borders. Our HTSPF utilizes the harmonic mean intensities of the image that result in effective segmentation of low contrast images. Using level set like SBGFRLS method and the harmonic mean intensities of the image like ACMHM method, our HTSPF performs better in cases of images having objects of blurred borders, multiple objects with diverse intensities and objects having low contrast. To regularize the level set function, we utilized the Gaussian filter. It also removes the need of expensive re-initialization technique. The proposed method is tested on synthetic and real images and its segmentation results demonstrate that the proposed method is robust in segmentation of images having objects of blurred borders, objects of low contrast and multiple objects with diverse intensities.
Although the empirical mode decomposition has been successfully applied to signal analysis, and the fusion applications, there is currently no efficient solution for color images fusion. This paper proposes a method b...
详细信息
暂无评论