L. Vivona, Donato Cascio, S. Bruno, A. Fauci, V. Taormina, A. Elgaaied, Y. Gorgi, R. Triki, M. B. Ahmed, S. Yalaoui, Maria Catanzaro, I. Brusca, G. Amato, G. Friscia, F. Fauci, G. Raso
{"title":"Unsupervised clustering method for pattern recognition in IIF images","authors":"L. Vivona, Donato Cascio, S. Bruno, A. Fauci, V. Taormina, A. Elgaaied, Y. Gorgi, R. Triki, M. B. Ahmed, S. Yalaoui, Maria Catanzaro, I. Brusca, G. Amato, G. Friscia, F. Fauci, G. Raso","doi":"10.1109/IPAS.2016.7880124","DOIUrl":"https://doi.org/10.1109/IPAS.2016.7880124","url":null,"abstract":"Autoimmune diseases are a family of more than 80 chronic, and often disabling, illnesses that develop when underlying defects in the immune system lead the body to attack its own organs, tissues, and cells. Diagnosis of autoimmune pathologies is based on research and identification of antinuclear antibodies (ANA) through indirect immunofluorescence (IIF) method and is performed by analyzing patterns and fluorescence intensity. We propose here a method to automatically classify the centromere pattern based on the grouping of centromeres on the cells through a clustering K-means algorithm. The described method was tested on a public database (MIVIA). The results of the test showed an Accuracy equal to (92.0 ± 1.0)%. Comparing our results with the results obtained on the MIVIA database it is possible to note that our method has a performance comparable with the three best values obtained. Indeed, the method here proposed allows an automatic segmentation and counting of the cells in the images, while the participants to the contest received the training set with the original images of the cells already segmented by specialists.","PeriodicalId":283737,"journal":{"name":"2016 International Image Processing, Applications and Systems (IPAS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133769409","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}
Ibtissem Wali, A. Kessentini, M. A. B. Ayed, N. Masmoudi
{"title":"Statistical analysis of SHVC encoded video","authors":"Ibtissem Wali, A. Kessentini, M. A. B. Ayed, N. Masmoudi","doi":"10.1109/IPAS.2016.7880119","DOIUrl":"https://doi.org/10.1109/IPAS.2016.7880119","url":null,"abstract":"Scalable extension (SHVC) of the High Efficiency Video Coding HEVC was developed to ameliorate the coding efficiency for different types of scalability. In this paper, a survey for SHVC extensions is investigated. We describe its scalability types and explain the different additional coding features that further improve the Enhancement Layer (EL) coding efficiency. Furthermore, we evaluate and prove the effectiveness of the SHVC through experimental results for different coding configurations reduction of about. Based on statistical analysis, depth 0 (64×64) can reach more than 75% of use in B1 frame. This statistics helped us explore deeply on the prediction mode percentages.","PeriodicalId":283737,"journal":{"name":"2016 International Image Processing, Applications and Systems (IPAS)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123548972","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}
Vinh Truong Hoang, A. Porebski, N. Vandenbroucke, D. Hamad
{"title":"LBP parameter tuning for texture analysis of lace images","authors":"Vinh Truong Hoang, A. Porebski, N. Vandenbroucke, D. Hamad","doi":"10.1109/IPAS.2016.7880063","DOIUrl":"https://doi.org/10.1109/IPAS.2016.7880063","url":null,"abstract":"Analysis of lace texture images is a challenging problem because the lace is a soft and extensible material and can be easily deformed. This paper investigates a whole system for lace classification. A first step, based on Otsu's segmentation method, allows to remove the background. Then the lace texture is characterized using local binary patterns (LBP). In order to be robust against rotation the Fourier Transform is applied on LBP histograms. The magnitude spectrum of this transform is then used as a feature vector. LBP descriptor parameters, including radius and number of neighbors, are adjusted in order to improve their relevance. The experiments show that the features based on LBP, with appropriate settings, produced good results in supervised and unsupervised contexts.","PeriodicalId":283737,"journal":{"name":"2016 International Image Processing, Applications and Systems (IPAS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116999535","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}
{"title":"A pretreatment using saliency map Harris to improve MSU blocking metric performance for encoding H264 / AVC : Saliency map for video quality assessment","authors":"M. Amor, F. Kammoun, Nouri Masmodi","doi":"10.1109/IPAS.2016.7880121","DOIUrl":"https://doi.org/10.1109/IPAS.2016.7880121","url":null,"abstract":"In this paper we are interested in establishing a pretreatment for existing metrics without reference (MSU Blocking Metric) for the H.264/MPEG-4 (Motion Picture Expert Group) AVC (Advanced Video Coding) standard. We perform a pretreatment using HARRIS saliency map to improve the performance of this metric. We evaluate the performance of the proposed pretreatment by using subjective “LIVE” video databases. The performance metrics, i.e. Pearson (PLCC) and Spearman correlation coefficients (SROCC) indicate that the pretreatment gives a good performance in H264 codec distortions.","PeriodicalId":283737,"journal":{"name":"2016 International Image Processing, Applications and Systems (IPAS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116956286","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}
Souhir Gabsi, Anissa Sghaier, Z. Medien, Mohsen Machhout
{"title":"Efficient software implementation of the final exponentiation for pairing","authors":"Souhir Gabsi, Anissa Sghaier, Z. Medien, Mohsen Machhout","doi":"10.1109/IPAS.2016.7880138","DOIUrl":"https://doi.org/10.1109/IPAS.2016.7880138","url":null,"abstract":"Pairing-based cryptography has got a lot of attention the last years, since the proposition of the tripartite key exchange. The best type of pairing is optimal ate pairing over Barreto-Naehrig curves which are based on two steps: Miller Loop and final exponentiation. Most of the researches were done for the Miller Loop. In this paper, we present the different methods for computing the hard part of the final exponentiation of optimal ate pairings based on a hard mathematical study. Using a comparative study based on the temporary number and memory resources, we will choose the best method to be then implemented in Matlab Software. Thus, the best one is Devigili et al. method presenting a reduced complexity and required number of registers.","PeriodicalId":283737,"journal":{"name":"2016 International Image Processing, Applications and Systems (IPAS)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128801004","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}
Lamia Rzouga Haddada, Imen Hamrouni Trimech, N. Amara
{"title":"A biometric watermarking approach of fingerprint images by DLDA Gabor face features without altering minutiae","authors":"Lamia Rzouga Haddada, Imen Hamrouni Trimech, N. Amara","doi":"10.1109/IPAS.2016.7880135","DOIUrl":"https://doi.org/10.1109/IPAS.2016.7880135","url":null,"abstract":"In this paper we propose a new approach for watermarking biometric fingerprint images using Gabor direct linear discriminant analysis face features. Our goal is to incorporate a watermark in the best embedding domain that preserves minutiae, which are the most relevant proven features of a fingerprint. We conducted a comprehensive study based on the influence of the watermark embedding domain choice on the performance of the minutiae-based identity and of the robustness and imperceptibility of the watermarking approach. Three embedding domains were tested: spatial, frequency and multiresolution. The various tests were performed on two biometric databases, multimodal and chimerical. The best results were recorded in the multiresolution domain in terms of preserving the minutiae number and positions. Moreover, this embedding domain led to the best verification performances and to a good compromise between robustness and imperceptibility.","PeriodicalId":283737,"journal":{"name":"2016 International Image Processing, Applications and Systems (IPAS)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130335726","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}
{"title":"Analysis of the use of some statistical measures in deciding about the efficiency of an image encryption algorithm","authors":"B. Nini, Asma Zitouni, Asma Ounzar","doi":"10.1109/IPAS.2016.7880130","DOIUrl":"https://doi.org/10.1109/IPAS.2016.7880130","url":null,"abstract":"Most of papers on image encryption provide some measures to attest that the presented works satisfy the required criteria in the field. Some others propose a comparative study and decide on whether one work is better than another one always using these measures. These last are of different types where the correlation coefficient is one among them. It is a statistical measure used to analyze the resemblance between neighboring pixels in an obtained cipher. In this paper, we give a study about the relevance of this criterion to the decision about the quality of an algorithm. We demonstrate that its importance is limited to have an idea about the resulting decorrelation. However, its use to decide about the quality of the algorithm, or to compare it to another one is not possible. We show that any calculated value is surrounded by randomness.","PeriodicalId":283737,"journal":{"name":"2016 International Image Processing, Applications and Systems (IPAS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134555235","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}
Marwa Braiki, A. Benzinou, K. Nasreddine, S. Labidi
{"title":"A comparative evaluation of segmentation methods for dendritic cells identification from microscopic images","authors":"Marwa Braiki, A. Benzinou, K. Nasreddine, S. Labidi","doi":"10.1109/IPAS.2016.7880129","DOIUrl":"https://doi.org/10.1109/IPAS.2016.7880129","url":null,"abstract":"Public health is one of the major concerns at the world level. Toxicology is an extremely challenging issue regarding that toxic substances are harmful to human health. In fact, toxicology studies are indispensable to evaluate the toxic effects on humans. Currently, a new evaluation technique based on the analysis of dendritic cells in vitro has been found by researchers. This analysis that remains purely visual is a tedious process, subjective and time-consuming. Therefore, an assessment tool for the analysis of toxic impact using automatic processing techniques by image analysis can be greatly useful for expert biologists. The foremost aim of this paper is to propose two segmentation approaches of dendritic cells from microscopic images and to present a comparative evaluation of them. The first suggested algorithm is based on automatic thresholding and mathematical morphology, while the second one combines the k-means clustering, thresholding and mathematical morphology based operations. For validation purposes, four performance measures were used to assess the obtained segmentation results with the ground truth images, elaborated by expert. Quantitatively, results show that the two suggested algorithms are efficient in identifying dendritic cells from 26 gray-scale images with a segmentation accuracy of 99.00 % and 99.37%, respectively.","PeriodicalId":283737,"journal":{"name":"2016 International Image Processing, Applications and Systems (IPAS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122715430","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}
Chiraz Massoud, Anissa Sghaier, Z. Medien, Mohsen Machhout
{"title":"Efficient software implementation of RNS-montgomery modular multiplication for embedded system","authors":"Chiraz Massoud, Anissa Sghaier, Z. Medien, Mohsen Machhout","doi":"10.1109/IPAS.2016.7880137","DOIUrl":"https://doi.org/10.1109/IPAS.2016.7880137","url":null,"abstract":"Recently, a lot of progress has been made in the implementation of asymmetric cryptography such that RSA or ECC (Elliptic Curve Cryptography) in both hardware and software. The Residue Number Systems (RNS) offer, many features make it very useful in cryptographic applications. Since the modular multiplication is the main operation, in this paper, we describe a Montgomery modular multiplication algorithm based on RNS. Then we implemented our design in TM i3 CPU, it computed the modular multiplication in only 9 ms (latency) and achieving maximum throughput of 528.","PeriodicalId":283737,"journal":{"name":"2016 International Image Processing, Applications and Systems (IPAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129113900","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}