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	Author	Susana Alvarez; Anna Salvatella; Maria Vanrell; Xavier Otazu
	Title	3D Texton Spaces for color-texture retrieval			Type	Conference Article
	Year	2010	Publication	7th International Conference on Image Analysis and Recognition	Abbreviated Journal
	Volume	6111	Issue		Pages	354–363
	Keywords
	Abstract	Color and texture are visual cues of different nature, their integration in an useful visual descriptor is not an easy problem. One way to combine both features is to compute spatial texture descriptors independently on each color channel. Another way is to do the integration at the descriptor level. In this case the problem of normalizing both cues arises. In this paper we solve the latest problem by fusing color and texture through distances in texton spaces. Textons are the attributes of image blobs and they are responsible for texture discrimination as defined in Julesz’s Texton theory. We describe them in two low-dimensional and uniform spaces, namely, shape and color. The dissimilarity between color texture images is computed by combining the distances in these two spaces. Following this approach, we propose our TCD descriptor which outperforms current state of art methods in the two different approaches mentioned above, early combination with LBP and late combination with MPEG-7. This is done on an image retrieval experiment over a highly diverse texture dataset from Corel.
	Address
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor	A.C. Campilho and M.S. Kamel
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-13771-6	Medium
	Area		Expedition		Conference	ICIAR
	Notes	CIC			Approved	no
	Call Number	CAT @ cat @ ASV2010a			Serial	1325
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	Author	Naveen Onkarappa; Angel Sappa
	Title	On-Board Monocular Vision System Pose Estimation through a Dense Optical Flow			Type	Conference Article
	Year	2010	Publication	7th International Conference on Image Analysis and Recognition	Abbreviated Journal
	Volume	6111	Issue		Pages	230-239
	Keywords
	Abstract	This paper presents a robust technique for estimating on-board monocular vision system pose. The proposed approach is based on a dense optical flow that is robust against shadows, reflections and illumination changes. A RANSAC based scheme is used to cope with the outliers in the optical flow. The proposed technique is intended to be used in driver assistance systems for applications such as obstacle or pedestrian detection. Experimental results on different scenarios, both from synthetic and real sequences, shows usefulness of the proposed approach.
	Address	Povoa de Varzim (Portugal)
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-13771-6	Medium
	Area		Expedition		Conference	ICIAR
	Notes	ADAS			Approved	no
	Call Number	ADAS @ adas @ OnS2010			Serial	1342
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	Author	Carles Sanchez;F. Javier Sanchez; Antoni Rosell; Debora Gil
	Title	An illumination model of the trachea appearance in videobronchoscopy images			Type	Book Chapter
	Year	2012	Publication	Image Analysis and Recognition	Abbreviated Journal	LNCS
	Volume	7325	Issue		Pages	313-320
	Keywords	Bronchoscopy, tracheal ring, stenosis assesment, trachea appearance model, segmentation
	Abstract	Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways. This imaging modality provides realistic images and allows non-invasive minimal intervention procedures. Tracheal procedures are routinary interventions that require assessment of the percentage of obstructed pathway for injury (stenosis) detection. Visual assessment in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error. This paper introduces an automatic method for the estimation of steneosed trachea percentage reduction in videobronchoscopic images. We look for tracheal rings , whose deformation determines the degree of obstruction. For ring extraction , we present a ring detector based on an illumination and appearance model. This model allows us to parametrise the ring detection. Finally, we can infer optimal estimation parameters for any video resolution.
	Address	Aveiro, Portugal
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title	Lecture Notes in Computer Science	Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-31297-7	Medium
	Area	800	Expedition		Conference	ICIAR
	Notes	MV;IAM			Approved	no
	Call Number	IAM @ iam @ SSR2012			Serial	1898
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	Author	Patricia Marquez; Debora Gil ; Aura Hernandez-Sabate
	Title	Error Analysis for Lucas-Kanade Based Schemes			Type	Conference Article
	Year	2012	Publication	9th International Conference on Image Analysis and Recognition	Abbreviated Journal
	Volume	7324	Issue	I	Pages	184-191
	Keywords	Optical flow, Confidence measure, Lucas-Kanade, Cardiac Magnetic Resonance
	Abstract	Optical flow is a valuable tool for motion analysis in medical imaging sequences. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in medical sequences. This paper presents an error analysis of Lucas-Kanade schemes in terms of intrinsic design errors and numerical stability of the algorithm. Our analysis provides a confidence measure that is naturally correlated to the accuracy of the flow field. Our experiments show the higher predictive value of our confidence measure compared to existing measures.
	Address	Aveiro, Portugal
	Corporate Author				Thesis
	Publisher	Springer-Verlag Berlin Heidelberg	Place of Publication		Editor
	Language	english	Summary Language		Original Title
	Series Editor	Campilho, Aurélio and Kamel, Mohamed	Series Title	Lecture Notes in Computer Science	Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-31294-6	Medium
	Area		Expedition		Conference	ICIAR
	Notes	IAM			Approved	no
	Call Number	IAM @ iam @ MGH2012a			Serial	1899
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	Author	Ricard Borras; Agata Lapedriza; Laura Igual
	Title	Depth Information in Human Gait Analysis: An Experimental Study on Gender Recognition			Type	Conference Article
	Year	2012	Publication	9th International Conference on Image Analysis and Recognition	Abbreviated Journal
	Volume	7325	Issue	II	Pages	98-105
	Keywords
	Abstract	This work presents DGait, a new gait database acquired with a depth camera. This database contains videos from 53 subjects walking in different directions. The intent of this database is to provide a public set to explore whether the depth can be used as an additional information source for gait classification purposes. Each video is labelled according to subject, gender and age. Furthermore, for each subject and view point, we provide initial and final frames of an entire walk cycle. On the other hand, we perform gait-based gender classification experiments with DGait database, in order to illustrate the usefulness of depth information for this purpose. In our experiments, we extract 2D and 3D gait features based on shape descriptors, and compare the performance of these features for gender identification, using a Kernel SVM. The obtained results show that depth can be an information source of great relevance for gait classification problems.
	Address	Aveiro, Portugal
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-31297-7	Medium
	Area		Expedition		Conference	ICIAR
	Notes	OR; MILAB;MV			Approved	no
	Call Number	Admin @ si @ BLI2012			Serial	2009
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	Author	Fernando Barrera; Felipe Lumbreras; Angel Sappa
	Title	Evaluation of Similarity Functions in Multimodal Stereo			Type	Conference Article
	Year	2012	Publication	9th International Conference on Image Analysis and Recognition	Abbreviated Journal
	Volume	7324	Issue	I	Pages	320-329
	Keywords	Aveiro, Portugal
	Abstract	This paper presents an evaluation framework for multimodal stereo matching, which allows to compare the performance of four similarity functions. Additionally, it presents details of a multimodal stereo head that supply thermal infrared and color images, as well as, aspects of its calibration and rectification. The pipeline includes a novel method for the disparity selection, which is suitable for evaluating the similarity functions. Finally, a benchmark for comparing different initializations of the proposed framework is presented. Similarity functions are based on mutual information, gradient orientation and scale space representations. Their evaluation is performed using two metrics: i) disparity error, and ii) number of correct matches on planar regions. In addition to the proposed evaluation, the current paper also shows that 3D sparse representations can be recovered from such a multimodal stereo head.
	Address
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-31294-6	Medium
	Area		Expedition		Conference	ICIAR
	Notes	ADAS			Approved	no
	Call Number	BLS2012a			Serial	2014
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	Author	Miguel Oliveira; Angel Sappa; V. Santos
	Title	Color Correction using 3D Gaussian Mixture Models			Type	Conference Article
	Year	2012	Publication	9th International Conference on Image Analysis and Recognition	Abbreviated Journal
	Volume	7324	Issue	I	Pages	97-106
	Keywords
	Abstract	The current paper proposes a novel color correction approach based on a probabilistic segmentation framework by using 3D Gaussian Mixture Models. Regions are used to compute local color correction functions, which are then combined to obtain the final corrected image. The proposed approach is evaluated using both a recently published metric and two large data sets composed of seventy images. The evaluation is performed by comparing our algorithm with eight well known color correction algorithms. Results show that the proposed approach is the highest scoring color correction method. Also, the proposed single step 3D color space probabilistic segmentation reduces processing time over similar approaches.
	Address
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	10.1007/978-3-642-31295-3_12	Medium
	Area		Expedition		Conference	ICIAR
	Notes	ADAS			Approved	no
	Call Number	Admin @ si @ OSS2012a			Serial	2015
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	Author	Laura Igual; Joan Carles Soliva; Roger Gimeno; Sergio Escalera; Oscar Vilarroya; Petia Radeva
	Title	Automatic Internal Segmentation of Caudate Nucleus for Diagnosis of Attention Deficit Hyperactivity Disorder			Type	Conference Article
	Year	2012	Publication	9th International Conference on Image Analysis and Recognition	Abbreviated Journal
	Volume	7325	Issue	II	Pages	222-229
	Keywords
	Abstract	Poster Studies on volumetric brain Magnetic Resonance Imaging (MRI) showed neuroanatomical abnormalities in pediatric Attention-Deficit/Hyperactivity Disorder (ADHD). In particular, the diminished right caudate volume is one of the most replicated findings among ADHD samples in morphometric MRI studies. In this paper, we propose a fully-automatic method for internal caudate nucleus segmentation based on machine learning. Moreover, the ratio between right caudate body volume and the bilateral caudate body volume is applied in a ADHD diagnostic test. We separately validate the automatic internal segmentation of caudate in head and body structures and the diagnostic test using real data from ADHD and control subjects. As a result, we show accurate internal caudate segmentation and similar performance among the proposed automatic diagnostic test and the manual annotation.
	Address	Aveiro, Portugal
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-31297-7	Medium
	Area		Expedition		Conference	ICIAR
	Notes	OR; HuPBA; MILAB			Approved	no
	Call Number	Admin @ si @ ISG2012			Serial	2059
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	Author	Francesco Brughi; Debora Gil; Llorenç Badiella; Eva Jove Casabella; Oriol Ramos Terrades
	Title	Exploring the impact of inter-query variability on the performance of retrieval systems			Type	Conference Article
	Year	2014	Publication	11th International Conference on Image Analysis and Recognition	Abbreviated Journal
	Volume	8814	Issue		Pages	413–420
	Keywords
	Abstract	This paper introduces a framework for evaluating the performance of information retrieval systems. Current evaluation metrics provide an average score that does not consider performance variability across the query set. In this manner, conclusions lack of any statistical significance, yielding poor inference to cases outside the query set and possibly unfair comparisons. We propose to apply statistical methods in order to obtain a more informative measure for problems in which different query classes can be identified. In this context, we assess the performance variability on two levels: overall variability across the whole query set and specific query class-related variability. To this end, we estimate confidence bands for precision-recall curves, and we apply ANOVA in order to assess the significance of the performance across different query classes.
	Address	Algarve; Portugal; October 2014
	Corporate Author				Thesis
	Publisher	Springer International Publishing	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-319-11757-7	Medium
	Area		Expedition		Conference	ICIAR
	Notes	IAM; DAG; 600.060; 600.061; 600.077; 600.075			Approved	no
	Call Number	Admin @ si @ BGB2014			Serial	2559
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	Author	Gioacchino Vino; Angel Sappa
	Title	Revisiting Harris Corner Detector Algorithm: a Gradual Thresholding Approach			Type	Conference Article
	Year	2013	Publication	10th International Conference on Image Analysis and Recognition	Abbreviated Journal
	Volume	7950	Issue		Pages	354-363
	Keywords
	Abstract	This paper presents an adaptive thresholding approach intended to increase the number of detected corners, while reducing the amount of those ones corresponding to noisy data. The proposed approach works by using the classical Harris corner detector algorithm and overcome the difficulty in finding a general threshold that work well for all the images in a given data set by proposing a novel adaptive thresholding scheme. Initially, two thresholds are used to discern between strong corners and flat regions. Then, a region based criteria is used to discriminate between weak corners and noisy points in the midway interval. Experimental results show that the proposed approach has a better capability to reject false corners and, at the same time, to detect weak ones. Comparisons with the state of the art are provided showing the validity of the proposed approach.
	Address	Póvoa de Varzim; Portugal; June 2013
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-39093-7	Medium
	Area		Expedition		Conference	ICIAR
	Notes	ADAS; 600.055			Approved	no
	Call Number	Admin @ si @ ViS2013			Serial	2562
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	Author	Stefan Schurischuster; Beatriz Remeseiro; Petia Radeva; Martin Kampel
	Title	A Preliminary Study of Image Analysis for Parasite Detection on Honey Bees			Type	Conference Article
	Year	2018	Publication	15th International Conference on Image Analysis and Recognition	Abbreviated Journal
	Volume	10882	Issue		Pages	465-473
	Keywords
	Abstract	Varroa destructor is a parasite harming bee colonies. As the worldwide bee population is in danger, beekeepers as well as researchers are looking for methods to monitor the health of bee hives. In this context, we present a preliminary study to detect parasites on bee videos by means of image analysis and machine learning techniques. For this purpose, each video frame is analyzed individually to extract bee image patches, which are then processed to compute image descriptors and finally classified into mite and no mite bees. The experimental results demonstrated the adequacy of the proposed method, which will be a perfect stepping stone for a further bee monitoring system.
	Address	Povoa de Varzim; Portugal; June 2018
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	ICIAR
	Notes	MILAB; no proj			Approved	no
	Call Number	Admin @ si @ SRR2018a			Serial	3110
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	Author	Patricia Suarez; Angel Sappa; Boris X. Vintimilla
	Title	Vegetation Index Estimation from Monospectral Images			Type	Conference Article
	Year	2018	Publication	15th International Conference on Images Analysis and Recognition	Abbreviated Journal
	Volume	10882	Issue		Pages	353-362
	Keywords
	Abstract	This paper proposes a novel approach to estimate Normalized Difference Vegetation Index (NDVI) from just the red channel of a RGB image. The NDVI index is defined as the ratio of the difference of the red and infrared radiances over their sum. In other words, information from the red channel of a RGB image and the corresponding infrared spectral band are required for its computation. In the current work the NDVI index is estimated just from the red channel by training a Conditional Generative Adversarial Network (CGAN). The architecture proposed for the generative network consists of a single level structure, which combines at the final layer results from convolutional operations together with the given red channel with Gaussian noise to enhance details, resulting in a sharp NDVI image. Then, the discriminative model estimates the probability that the NDVI generated index came from the training dataset, rather than the index automatically generated. Experimental results with a large set of real images are provided showing that a Conditional GAN single level model represents an acceptable approach to estimate NDVI index.
	Address	Povoa de Varzim; Portugal; June 2018
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	ICIAR
	Notes	MSIAU; 600.086; 600.130; 600.122			Approved	no
	Call Number	Admin @ si @ SSV2018c			Serial	3196
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	Author	Rafael E. Rivadeneira; Patricia Suarez; Angel Sappa; Boris X. Vintimilla
	Title	Thermal Image SuperResolution Through Deep Convolutional Neural Network			Type	Conference Article
	Year	2019	Publication	16th International Conference on Images Analysis and Recognition	Abbreviated Journal
	Volume		Issue		Pages	417-426
	Keywords
	Abstract	Due to the lack of thermal image datasets, a new dataset has been acquired for proposed a super-resolution approach using a Deep Convolution Neural Network schema. In order to achieve this image enhancement process, a new thermal images dataset is used. Different experiments have been carried out, firstly, the proposed architecture has been trained using only images of the visible spectrum, and later it has been trained with images of the thermal spectrum, the results showed that with the network trained with thermal images, better results are obtained in the process of enhancing the images, maintaining the image details and perspective. The thermal dataset is available at http://www. cidis.espol.edu.ec/es/dataset.
	Address	Waterloo; Canada; August 2019
	Corporate Author				Thesis
	Publisher		Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	ICIAR
	Notes	MSIAU; 600.130; 601.349; 600.122			Approved	no
	Call Number	Admin @ si @ RSS2019			Serial	3269
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	Author	Sergio Escalera; Alicia Fornes; Oriol Pujol; Petia Radeva
	Title	Multi-class Binary Symbol Classification with Circular Blurred Shape Models			Type	Conference Article
	Year	2009	Publication	15th International Conference on Image Analysis and Processing	Abbreviated Journal
	Volume	5716	Issue		Pages	1005–1014
	Keywords
	Abstract	Multi-class binary symbol classification requires the use of rich descriptors and robust classifiers. Shape representation is a difficult task because of several symbol distortions, such as occlusions, elastic deformations, gaps or noise. In this paper, we present the Circular Blurred Shape Model descriptor. This descriptor encodes the arrangement information of object parts in a correlogram structure. A prior blurring degree defines the level of distortion allowed to the symbol. Moreover, we learn the new feature space using a set of Adaboost classifiers, which are combined in the Error-Correcting Output Codes framework to deal with the multi-class categorization problem. The presented work has been validated over different multi-class data sets, and compared to the state-of-the-art descriptors, showing significant performance improvements.
	Address	Salerno, Italy
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-04145-7	Medium
	Area		Expedition		Conference	ICIAP
	Notes	MILAB;HuPBA;DAG			Approved	no
	Call Number	BCNPCL @ bcnpcl @ EFP2009c			Serial	1186
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	Author	L.Tarazon; D. Perez; N. Serrano; V. Alabau; Oriol Ramos Terrades; A. Sanchis; A. Juan
	Title	Confidence Measures for Error Correction in Interactive Transcription of Handwritten Text			Type	Conference Article
	Year	2009	Publication	15th International Conference on Image Analysis and Processing	Abbreviated Journal
	Volume	5716	Issue		Pages	567-574
	Keywords
	Abstract	An effective approach to transcribe old text documents is to follow an interactive-predictive paradigm in which both, the system is guided by the human supervisor, and the supervisor is assisted by the system to complete the transcription task as efficiently as possible. In this paper, we focus on a particular system prototype called GIDOC, which can be seen as a first attempt to provide user-friendly, integrated support for interactive-predictive page layout analysis, text line detection and handwritten text transcription. More specifically, we focus on the handwriting recognition part of GIDOC, for which we propose the use of confidence measures to guide the human supervisor in locating possible system errors and deciding how to proceed. Empirical results are reported on two datasets showing that a word error rate not larger than a 10% can be achieved by only checking the 32% of words that are recognised with less confidence.
	Address	Vietri sul Mare, Italy
	Corporate Author				Thesis
	Publisher	Springer Berlin Heidelberg	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN	0302-9743	ISBN	978-3-642-04145-7	Medium
	Area		Expedition		Conference	ICIAP
	Notes	DAG			Approved	no
	Call Number	Admin @ si @ TPS2009			Serial	1871
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