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2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA)最新文献

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Image processing-based monitoring of a batch flotation process 基于图像处理的间歇浮选过程监控
2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA) Pub Date : 2013-03-06 DOI: 10.1109/PRIA.2013.6528458
M. Massinaei, N. Mehrshad, M. Hosseini
{"title":"Image processing-based monitoring of a batch flotation process","authors":"M. Massinaei, N. Mehrshad, M. Hosseini","doi":"10.1109/PRIA.2013.6528458","DOIUrl":"https://doi.org/10.1109/PRIA.2013.6528458","url":null,"abstract":"Machine vision technology now offers a viable means of monitoring and controlling flotation performance. In this study an image analysis algorithm utilizing an adaptive marker based watershed transform was developed to segment the froth images and measure the bubble size over a wide range of process conditions. Flotation experiments were conducted at a wide range of operating conditions (i.e. gas flow rate, slurry solids %, frother dosage and collector dosage) and the froth mean bubble size was determined for each run. The results showed that the proposed algorithm can be successfully applied to monitor the flotation process at different conditions.","PeriodicalId":370476,"journal":{"name":"2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125927311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Application of inclined planes system optimization on data clustering 斜面系统优化在数据聚类中的应用
2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA) Pub Date : 2013-03-06 DOI: 10.1109/PRIA.2013.6528451
M. Mozaffari, H. Abdy, S. Zahiri
{"title":"Application of inclined planes system optimization on data clustering","authors":"M. Mozaffari, H. Abdy, S. Zahiri","doi":"10.1109/PRIA.2013.6528451","DOIUrl":"https://doi.org/10.1109/PRIA.2013.6528451","url":null,"abstract":"Data-mining is a branch of science which tends to extract a series of futures and some meaningful information from a huge database in proper time and cost. Clustering is one of the popular methods in this field. The purpose of clustering is to use a database and group together its items with similar characteristics. Application of clustering in many fields of science and engineering problems like Pattern recognition, data retrieval, bio-informatics, machine learning and the Internet cause to have significantly developed in the last decades. A rapid growth in the volume of information in databases revealed weakness of traditional methods like K-means in facing with huge data. In this paper a new clustering method based on the Inclined Planes system Optimization algorithm was proposed and evaluate on a series of standard datasets. Comparison study revealed a significant superiority over other similar clustering algorithms.","PeriodicalId":370476,"journal":{"name":"2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114605937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 14
Persian handwritten numeral recognition using Complex Neural Network and non-linear feature extraction 波斯语手写数字识别采用复杂神经网络和非线性特征提取
2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA) Pub Date : 2013-03-06 DOI: 10.1109/PRIA.2013.6528447
Z. Shokoohi, A. M. Hormat, F. Mahmoudi, H. Badalabadi
{"title":"Persian handwritten numeral recognition using Complex Neural Network and non-linear feature extraction","authors":"Z. Shokoohi, A. M. Hormat, F. Mahmoudi, H. Badalabadi","doi":"10.1109/PRIA.2013.6528447","DOIUrl":"https://doi.org/10.1109/PRIA.2013.6528447","url":null,"abstract":"In this paper, we propose a new isolated handwritten numbers recognition by using of sparse structure representation. We introduce the sparse structure which is a over-complete dictionary and it is known with K-SVD algorithm. In this vocabulary, values adopted by initialized to the first layer of Complex Neural Network(CNN) and in the last, it learned for doing classification task. The distinction between proposed method with previous methods in addition to using of the CNN and K-SVD algorithm is non-linear feature extraction. It is noted which in the previous methods extracted linear feature. When using of each type linear and non-linear analysis, it is important that we distinguish between their application In reduce dimensional and special gregarious correct recognition of the features that doing basis on specific rules. Subspaces under high power will appears in the first usage, for notice to denoising and high data compression Without necessary that individuals were specifically. this is only condition which in describe the subspace to size of information in the data.","PeriodicalId":370476,"journal":{"name":"2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116620126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
A modern approach to the diagnosis of breast cancer in women based on using Cellular Automata 基于细胞自动机的现代女性乳腺癌诊断方法
2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA) Pub Date : 2013-03-06 DOI: 10.1109/PRIA.2013.6528448
R. Hadi, S. Saeed, A. Hamid
{"title":"A modern approach to the diagnosis of breast cancer in women based on using Cellular Automata","authors":"R. Hadi, S. Saeed, A. Hamid","doi":"10.1109/PRIA.2013.6528448","DOIUrl":"https://doi.org/10.1109/PRIA.2013.6528448","url":null,"abstract":"Breast cancer is one of the most common conditions as well as one of the most important factors of death among women. If diagnosed correctly and in time, it may cause fewer death tolls. The most important method of diagnosing this type of cancer is using mammography imaging. In some cases, the diagnosis may be incorrect. In the present article, Cellular Automata is used for the diagnosis of breast cancer type micro-calsification (or tiny calcium particle sediments). In this approach the mammography image of the alleged patient is converted to an optimum image through preprocessing. Next, this image is entered into a cellular network to determine its cluster center. The results achieved by this approach on DDSM indicated that diagnosis based on the approach introduced in this article can be a useful combination for the traditional methods.","PeriodicalId":370476,"journal":{"name":"2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114650484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Edge detection of digital images using a conducted ant colony optimization and intelligent thresholding 基于蚁群优化和智能阈值的数字图像边缘检测
2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA) Pub Date : 2013-03-06 DOI: 10.1109/PRIA.2013.6528432
H. Reza-Alikhani, A. Naghsh, R. Jalali-Varnamkhasti
{"title":"Edge detection of digital images using a conducted ant colony optimization and intelligent thresholding","authors":"H. Reza-Alikhani, A. Naghsh, R. Jalali-Varnamkhasti","doi":"10.1109/PRIA.2013.6528432","DOIUrl":"https://doi.org/10.1109/PRIA.2013.6528432","url":null,"abstract":"An edge detection algorithm based on Ant Colony Optimization (ACO) and Fuzzy Inference System (FIS) and neural network is presented. This algorithm uses a FIS with 4 simple rules to identify the probable edge pixels in 4 main directions, then the ACO is applied for assigning a higher pheromone value for the probable edge pixels rather than other pixels so that the ants movement toward edge pixels get faster. Another factor that needs to be considered in order to conduct the ants' movement is the influence of the heuristic information in the movement of any ant to be proportional to local change in intensity of each pixel. Finally, by using an intelligent thresholding technique which is provided by training a neural network, the edges from the final pheromone matrix are extracted. Experimental results are provided in order to demonstrate the superior performance of the proposed approach.","PeriodicalId":370476,"journal":{"name":"2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115099303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
A novel evolutionary algorithm for block-based neural network training 一种新的基于块的神经网络训练进化算法
2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA) Pub Date : 2013-03-06 DOI: 10.1109/PRIA.2013.6528434
A. Niknam, P. Hoseini, B. Mashoufi, A. Khoei
{"title":"A novel evolutionary algorithm for block-based neural network training","authors":"A. Niknam, P. Hoseini, B. Mashoufi, A. Khoei","doi":"10.1109/PRIA.2013.6528434","DOIUrl":"https://doi.org/10.1109/PRIA.2013.6528434","url":null,"abstract":"A novel evolutionary algorithm with fixed genetic parameters rate have presented for block-based neural network (BbNN) training. This algorithm can be used in BbNN training which faces complicated problems such as simulation of equations, classification of signals, image processing and implementation of logic gates and so on. The fixed structure of our specific BbNN allows us to implement the trained network by a fixed circuit rather than utilizing a reconfigurable hardware which is usually employed in conventional designs. Avoiding the reconfigurable hardware leads to lower power consumption and chip area. All simulations are performed in MATLAB software.","PeriodicalId":370476,"journal":{"name":"2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129341658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
Image de-noising with virtual hexagonal image structure 基于虚拟六边形图像结构的图像去噪
2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA) Pub Date : 2013-03-06 DOI: 10.1109/PRIA.2013.6528440
M. Nourian, M. R. Aahmadzadeh
{"title":"Image de-noising with virtual hexagonal image structure","authors":"M. Nourian, M. R. Aahmadzadeh","doi":"10.1109/PRIA.2013.6528440","DOIUrl":"https://doi.org/10.1109/PRIA.2013.6528440","url":null,"abstract":"Up to several years ago, all images had certain square pixel structures and all processing works were done on the same basis. After a few years a new hexagonal pixel structure was introduced. Because of having more symmetry and several other benefits, the hexagonal structure is very highly regarded. Up to now many researchers have addressed many applications of this new structure, including rotation, scaling, and edge detection. In this paper, we apply this new structure and consider its application in de-noising. We also introduce a new method for de-noising images with hexagonal pixel structures. Then, we will compare the obtained results with images of square structures. Experimental results show that the proposed de-nosing algorithm on the image with hexagonal pixels improves Signal-to-Noise Ratio compared with de-noising square pixels algorithm.","PeriodicalId":370476,"journal":{"name":"2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127250178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
ROI soccer video compression using wavelet-domain block matching and EBCOT coding techniques in very low bit rate communication 在非常低的比特率通信中使用小波域块匹配和EBCOT编码技术的ROI足球视频压缩
2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA) Pub Date : 2013-03-06 DOI: 10.1109/PRIA.2013.6528430
H. Grailu, R. Soltani, M. Akrami
{"title":"ROI soccer video compression using wavelet-domain block matching and EBCOT coding techniques in very low bit rate communication","authors":"H. Grailu, R. Soltani, M. Akrami","doi":"10.1109/PRIA.2013.6528430","DOIUrl":"https://doi.org/10.1109/PRIA.2013.6528430","url":null,"abstract":"Today, a large amount of sport video data are produced which needs to be stored and/or transmitted in low bit rate applications such as internet communication. The Region-of-interest (ROI) video coding technique aims to relatively preserve the video quality, especially in desired regions. In other hand, in soccer videos only special regions have importance for the viewer. In this paper a novel ROI soccer video compression method is proposed which employs wavelet-domain block matching, shot boundary detection, Enhanced EBCOT coding, and region-of-interest detection techniques. The compression performance of the proposed method is compared to that of two conventional methods/standards of MPEG4 and FLV. Simulation results show that in fixed low bit rate of 8Kbps, the proposed method has about 1.5 dB higher average PSNR than that of the other ones.","PeriodicalId":370476,"journal":{"name":"2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132960972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Robust multiple human tracking using particle swarm optimization and the Kalman filter on full occlusion conditions 基于粒子群优化和卡尔曼滤波的全遮挡条件下的鲁棒多人跟踪
2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA) Pub Date : 2013-03-06 DOI: 10.1109/PRIA.2013.6528450
R. Serajeh, K. Faez, A. E. Ghahnavieh
{"title":"Robust multiple human tracking using particle swarm optimization and the Kalman filter on full occlusion conditions","authors":"R. Serajeh, K. Faez, A. E. Ghahnavieh","doi":"10.1109/PRIA.2013.6528450","DOIUrl":"https://doi.org/10.1109/PRIA.2013.6528450","url":null,"abstract":"Visual surveillance in crowded scenes, especially for humans, has recently been one of the most active research topics in machine vision because of its applications such as deter and response to crime, suspicious activities, terrorism or human behavior recognition. One of the most important problems in multiple human tracking is the occlusion problem. When the number of humans has an occlusion with each other or the background, the tracker should track them correctly. In this paper, we use particle swarm optimization (PSO) as a tracker, in addition to the Kalman filter and some other mathematical equations to solve the occlusion problem which the occlusion can be partially or completely. Experimental results on several real videos sequences from different conditions have shown the effectiveness of our approach.","PeriodicalId":370476,"journal":{"name":"2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131629183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Persian calligraphy using genetic algorithm 波斯书法使用遗传算法
2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA) Pub Date : 2013-03-06 DOI: 10.1109/PRIA.2013.6528427
Mohamadreza Mash'al, J. Sadri
{"title":"Persian calligraphy using genetic algorithm","authors":"Mohamadreza Mash'al, J. Sadri","doi":"10.1109/PRIA.2013.6528427","DOIUrl":"https://doi.org/10.1109/PRIA.2013.6528427","url":null,"abstract":"This project explores the use of evolutionary computation to design a calligraphic artwork. “Parand” allows the user to create art, without requiring any technical or artistic training. In using an evolutionary process to create the composition, the user has the option to choose whether he/she wants the program to make evaluations about the creations in each generation, or he/she wants to make the evaluations himself/herself. All the user needs to do in the latter case is to evaluate a number of possible creations that are generated at each generation to explore the design space. The work presented here illustrates the prototype system and examples of the art that may be created with it.","PeriodicalId":370476,"journal":{"name":"2013 First Iranian Conference on Pattern Recognition and Image Analysis (PRIA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132780249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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