Preprocesado Avanzado de Imágenes Laríngeas para Mejorar la Segmentación del Área Glotal

El presente trabajo describe un método avanzado de preprocesado de imagen para mejorar la detección automática del espacio glotal en imagines laríngeas. El sistema puede aplicarse a imágenes obtenidas a partir de exploraciones de alta velocidad o a partir de exploraciones estroboscópicas (baja velocidad), aunque es en estas últimas donde se observan las mayores ventajas, al tratarse de grabaciones de inferior calidad. Con esta nueva técnica de preprocesado se logran resolver ciertos fallos de segmentación producidos por un sistema previo basado en transformada “Watershed” y “Merging”. En resumen, se consiguen arreglar o mejorar el 38% de los errores de delineado de la glotis que aparecían en 29 imágenes de un total de 111 segmentadas

Salient region detection using contrast-based saliency and watershed segmentation

Salient region detection is useful for many applications such as image segmentation, compression, image retrieval, object tracking, and machine vision systems.In this paper, an approach to detect salient regions in a visual scene using contrast-based saliency and watershed segmentation is presented.The approach allows salient objects to be detected and extracted for analysis while preserving the actual boundaries of the salient objects. The approach can be executed in parallel making it efficient for real time applications

Detección del espacio glotal en imágenes laríngeas mediante transformada Watershed y Merging JND

El presente artículo describe un nuevo método para la detección del espacio glotal en imágenes laríngeas obtenidas de vídeos de alta o baja velocidad. El proceso de detección basa su eficacia en la combinación de varias técnicas de gran relevancia en el campo del tratamiento digital de imágenes. Una de estas técnicas es la transformada Watershed que junto con varios tipos de Merging y un proceso final de predicción lineal, hacen posible la detección automática en un 99% de las imágenes analizadas. La potencia del método se ve incrementada por la ausencia de cualquier tipo de inicialización y por no necesitar condiciones estrictas sobre las características de las imágenes a procesar. Evidentemente es importante que el algoritmo integre información a priori del espacio glotal, pero este conocimiento es bastante relajado comparado con las condiciones impuestas por otros trabajos que también intentan la segmentación

Segmentation of the glottal space from laryngeal images using the watershed transform

The present work describes a new method for the automatic detection of the glottal space from laryngeal images obtained either with high speed or with conventional video cameras attached to a laryngoscope. The detection is based on the combination of several relevant techniques in the field of digital image processing. The image is segmented with a watershed transform followed by a region merging, while the final decision is taken using a simple linear predictor. This scheme has successfully segmented the glottal space in all the test images used. The method presented can be considered a generalist approach for the segmentation of the glottal space because, in contrast with other methods found in literature, this approach does not need either initialization or finding strict environmental conditions extracted from the images to be processed. Therefore, the main advantage is that the user does not have to outline the region of interest with a mouse click. In any case, some a priori knowledge about the glottal space is needed, but this a priori knowledge can be considered weak compared to the environmental conditions fixed in former works

Analyses of the Watershed Transform

International audienceIn the framework of mathematical morphology, watershed transform (WT) represents a key step in image segmentation procedure. In this paper, we present a thorough analysis of some existing watershed approaches in the discrete case: WT based on flooding, WT based on path-cost minimization, watershed based on topology preservation, WT based on local condition and WT based on minimum spanning forest. For each approach, we present detailed description of processing procedure followed by mathematical foundations and algorithm of reference. Recent publications based on some approaches are also presented and discussed. Our study concludes with a classification of different watershed transform algorithms according to solution uniqueness, topology preservation, prerequisites minima computing and linearity

Prédiction de la teneur en anthocyane du fruit de la canneberge par vision par ordinateur

L'objectif de ce travail est d'établir une méthode non destructive, utilisant la vision par ordinateur, pour prédire le Tacy d'échantillons de canneberge. Une relation existe entre la couleur externe des fruits, leur calibre et le Tacy. Une caméra numérique a permis d'acquérir quatre photos par échantillon afin d'extraire la couleur et la surface des fruits. L'analyse par composantes principales suivie d'une régression linéaire a permis de modéliser la couleur canneberge sous forme d'échelle couleur. Le modèle prédictif du Tacy établi par régression linéaire multiple utilise la variable colorimétrique a* de l'espace ICCLAB (CIELAB encodé sur 8 bits) et la surface des fruits. En considérant un terme d'erreur type identique à celui de l'analyse chimique (± 3), ce modèle permet d'obtenir 100% de prédictions réussies sur les données de la saison de récolte 2005 en enlevant les données aberrantes, et 77% sur celles de 2006

Analysis of algorithms of the Watershed Transform

Orientador: Roberto de Alencar LotufoDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de ComputaçãoResumo: A transformada watershed é uma técnica morfológica de segmentação de imagens inspirada na divisão de superfícies em bacias hidrográficas, tendo diversas formas de definição e de algoritmos. Este trabalho realiza uma análise sistemática da literatura de catorze destes algoritmos. Foram consideradas as principais abordagens existentes desde a introdução do primeiro algoritmo rápido por Vincent e Soille em 1991, até os trabalhos de Cousty et al. em 2009. Para melhor compreensão da área, as definições de transformada watershed são revisitadas, provendo o conjunto de soluções formais possíveis e esperadas dos algoritmos. Na análise destes algoritmos é fornecido pseudocódigo com notação uniformizada e uma implementação operacional Python permitindo abstrair detalhes de programação. Além disto, três algoritmos foram corrigidos para melhor aderência a definição e especificação. Também são identificadas propriedades tais como o comportamento de varredura dos pixels, uso de estratégias em particular, uso de estruturas de dados, entre outras. A compilação das informações sobre os algoritmos permitiu generalizá-los e classificá-los baseado em paradigmas clássicos da computação, a saber a busca em largura e em profundidade. Ambos são embasados na ordem de visitação dos pixels utilizada, sendo a busca em largura semelhante a simulação de inundação enquanto a busca em profundidade simula gotas de água em uma superfície. Foram também realizados estudos comparativos entre as definições implementadas pelos algoritmos, entre as estratégias utilizadas para tratamento de problemas comuns, entre o desempenho obtido pelos programas Python, e de paralelismo e abordagens utilizadas neste último caso. Desta forma, produziu-se um panorama geral e atualizado dos algoritmos de transformada watershedAbstract: The watershed transform is a morphological image segmentation technique inspired on the division of surfaces in catchment basins, with several forms of definition and algorithms. This work accomplishes a survey of the literature on fourteen of these algorithms. The main approaches since the introduction of the first fast algorithm by Vincent and Soille in 1991, until the work of Cousty et al. in 2009 has been considered. For better understanding of the subject, the watershed definitions are revisited, providing the set of formal solutions that are possible and expected from the algorithms. On the analysis of the algorithms it is supplied pseudocode with a uniform notation and a Python operational implementation allowing to abstract programming details. Aside, three algorithms were corrected for better adherence to definition and specification. Also some properties such as the scanning behaviour, use of particular strategies, and use of data structures, among others were identified. The compilation of information of the algorithms allowed to generalise and classify them based on classic paradigms of computing, namely breadth-first and depth-first search. Both are based on the visiting order of the pixels, with the breadth-first similar to a flooding simulation while the depth-first simulates drops of water on a surfaceMestradoEngenharia de ComputaçãoMestre em Engenharia Elétric

Relationships Between Some Watershed Definitions And Their Tie-zone Transforms

To better understand the numerous solutions related to watershed transform (WT), this paper shows the relationships between some discrete definitions of the WT, especially those based on image foresting transform (IFT) with/without lexicographic cost function, topographic distance (TD), local condition (LC), flooding (F), and minimum spanning forest (MSF). Some of these paradigms allow multiple solutions. The tie-zone (TZ) transform returns a unique solution from a set of multiple solutions of a given WT. We demonstrate that the TZ transform applied to the IFT-WT includes all the solutions predicted by the other paradigms. More precisely, the watershed line of TD-WT and F-WT are contained in the TZ of the IFT-WT, while the catchment basins of TD-WT or F-WT contain the basins of the TZ-IFT-WT. In addition, the TD-WT can be seen as the tie-zone transform of the LC-WT. Furthermore, any solution of LC-WT or MSF-WT is also solution of the IFT-WT. Finally, MSF-WT and IFT-WT have the same tie-zone transform. © 2009 Elsevier B.V. All rights reserved.281014721482Beucher, S., Use of watersheds in contour detection (1979) International Workshop on Image Processing, Real-Time Edge and Motion Detection/Estimation, , Rennes, FranceBeucher, S., Meyer, F., The morphological approach to segmentation: The watershed transform (1993) Mathematical Morphology in Image Processing, pp. 433-481Meyer, F., Topographic distance and watershed lines (1994) Signal Processing, (38), pp. 113-125Najman, L., Schmitt, M., Watershed of a continuous function (1994) Signal Process, 38 (1), pp. 99-112Prêteux, F., On a distance function approach for gray-level mathematical morphology (1993) Mathematical Morphology in Image Processing, pp. 323-349Roerdink, J., Meijster, A., Algorithms and parallelization strategies (2000) Fundamenta Informaticae, 41 (12), pp. 187-228Lin, Y., Tsai, Y., Hung, Y., Shih, Z., Comparison between immersion-based and toboggan-based watershed image segmentation (2006) IEEE Transactions on Image Processing, 15 (3), pp. 632-640Osma Ruiz, V., Godino Llorente, J., Saenz Lechon, N., Gomez Vilda, P., An improved watershed algorithm based on efficient computation of shortest paths (2007) Pattern Recognition, 40 (3), pp. 1078-1090Vincent, L., Soille, P., Watersheds in digital spaces: An efficient algorithm based on immersion simulations (1991) IEEE Transactions on Pattern Analysis and Machine Intelligence, 13 (6), pp. 583-598Couprie, M., Bertrand, G., Topological grayscale watershed transformation (1997) SPIE Vision Geometry v Proceedings, 3168, pp. 136-146Lotufo, R., The ordered queue and the optimality of the watershed approaches (2000) 5th International Symposium on Mathematical Morphology, pp. 341-350. , Kluwer Academic, Palo Alto (CA), USAFalcão, A., Stolfi, J., Lotufo, R., The image foresting transform: Theory, algorithms, and applications (2004) IEEE Transactions on Pattern Analysis and Machine Intelligence, 26 (1), pp. 19-29Meyer, F., Minimum spanning forests for morphological segmentation (1994) Mathematical Morphology and Its Applications to Image Processing, pp. 77-84Audigier, R., Lotufo, R., Watershed by image foresting transform, tie-zone, and theoretical relationships with other watershed definitions (2007) Proceedings of the 8th International Symposium on Mathematical Morphology (ISMM'07), , Rio de Janeiro, BrazilFalcão, A., Da Cunha, B., Lotufo, R., Design of connected operators using the image foresting transform (2001) SPIE on Medical Imaging, 4322, pp. 468-479Audigier, R., Lotufo, R., Duality between the watershed by image foresting transform and the fuzzy connectedness segmentation approaches (2006) XIX Brazilian Symp. on Computer Graph. and Image Proc. (SIBGRAPI'06), pp. 53-60. , IEEE Press, Manaus, BrazilLotufo, R., IFT-watershed from gray-scale marker (2002) XV Brazilian Symp. on Computer Graph. and Image Proc., pp. 146-152. , IEEE Press, Fortaleza, BrazilAudigier, R., Lotufo, R., Uniquely-determined thinning of tie-zone watershed based on label frequency Journal of Mathematical Imaging and Vision, , doi: 10.1007/s10851-007-0780-4Audigier, R., Lotufo, R., Tie-zone watershed, bottlenecks and segmentation robustness analysis (2005) XVIII Brazilian Symp. on Computer Graph. and Image Proc. (SIBGRAPI'05), pp. 55-62. , IEEE Press, Natal, BrazilAudigier, R., Lotufo, R., Couprie, M., The tie-zone watershed: Definition, algorithm and applications (2005) Proceedings of IEEE International Conference on Image Processing (ICIP'05), 2, pp. 654-657. , Genova, ItalyBieniek, A., A parallel watershed algorithm (1997) Proc. 10th Scandinavian Conference on Image Analysis (SCIA'97), pp. 237-244. , Lappeenranta, FinlandBieniek, A., Moga, A., A connected component approach to the watershed segmentation (1998) Mathematical Morphology and Its Applications to Image and Signal Processing, pp. 215-222Gondran, M., Minoux, M., Trees and arborescences (1984) Graphs and Algorithms, pp. 129-159. , John Wiley and Sons LtdUdupa, J., Saha, P., Lotufo, R., Relative fuzzy connectedness and object definition: Theory, algorithms, and applications in image segmentation (2002) IEEE Transactions on Pattern Analysis and Machine Intelligence, 24 (11), pp. 1485-150

Analysis Of The Watershed Algorithms Based On The Breadth-first And Depth-first Exploring Methods

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)In this paper, fifteen watershed algorithms are reviewed. For clarity, first we expose two graph exploring methods modified to be guidelines for understanding the approaches taken by these algorithms: the breadth-first watershed and the depth-first watershed. Both paradigms rely on the visiting order applied by the algorithms. The breadth-first is more recognisable as a seed region growing or marker expansion process, grouping both methods based on flooding and hierarchical queue. The depth-first groups the algorithms based on the drop of water simulation, forming a simple path until a regional minimum is found. We analyse and classify fifteen algorithms, and two of them were better characterised. Along with this, some useful information (i.e. use of markers and line over pixel) is organised, in order to facilitate the choice of an algorithm. © 2009 IEEE.133140Petrobras,CNPq,CAPES,INCTMat,FAPERJConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Digabel, H., Lantuéjoul, C., Iterative algorithms (1978) Proc. Second European Symp. Quantitative Analysis of Microstructures in Material Science, Biology and Medicine, pp. 85-99. , J.-L. Chermant, Ed. Stuttgart, Germany: Riederer VerlagBeucher, S., Lantuéjoul, C., Use of watersheds in contour detection (1979) International Workshop on Image Processing: Real-time Edge and Motion Detection/Estimation, , Rennes, France, SeptemberMeyer, F., Beucher, S., Morphological segmentation (1990) Journal of Visual Communication and Image Representation, 1 (1), pp. 21-46. , SeptemberR. Audigier and R. A. Lotufo, Watershed by image foresting transform, tie-zone, and theoretical relationships with other watershed definitions, in ISMM'2007 Proceedings, 1, Universidade de São Paulo (USP). São José dos Campos: Instituto Nacional de Pesquisas Espaciais (INPE), October 2007Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C., (2001) Introduction to Algorithms, , 2nd ed. Cambridge, Massachusetts: The MIT PressVincent, L., Soille, P., Watersheds in digital spaces: An efficient algorithm based on immersion simulations (1991) IEEE Transactions on Pattern Analysis and Machine Intelligence, 13 (6), pp. 583-598S. Beucher and F. Meyer, Mathematical morphology in image processing, ser. Optical Engineering. New York: M. Dekker, 1993, ch. The Morphological Approach to Segmentation: The Watershed TransformationDijkstra, E., A note on two problems in connexion with graphs (1959) Numerische Mathematik, 1 (1), pp. 269-271. , DecemberLotufo, R., Falcão, A., The ordered queue and the optimality of the watershed approaches (2000) Proceedings of the 5th International Symposium on Mathematical Morphology and its Applications to Image and Signal Processing, 18, pp. 341-350. , Kluwer Academic Publishers, JuneFalcão, A.X., Stolfi, J., Lotufo, R.A., The image foresting transform: Theory, algorithms, and applications (2004) Pattern Analysis and Machine Intelligence, IEEE Transactions on, 26 (1), pp. 19-29Meyer, F., Topographic distance and watershed lines (1994) Signal Processing, 38 (1), pp. 113-125Lin, Y., Tsai, Y., Hung, Y., Shih, Z., Comparison between immersion-based and toboggan-based watershed image segmentation (2006) IEEE Transactions on Image Processing, 15 (3), pp. 632-640Meyer, F., Minimum spanning forests for morphological segmentation (1994) Mathematical morphology and its applications to image processing, 2, pp. 77-87. , J. Serra and P. Soille, Eds, Kluwer Academic PublishersBieniek, A., Moga, A., A connected component approach to the watershed segmentation (1998) ISMM '98: Proceedings of the fourth international symposium on Mathematical morphology and its applications to image and signal processing, pp. 215-222. , Norwell, MA, USA: Kluwer Academic PublishersBieniek, A., Moga, A., An efficient watershed algorithm based on connected components (2000) Pattern Recognition, 33 (6), pp. 907-916Meijster, A., Roerdink, J.B.T.M., A disjoint set algorithm for the watershed transform (1998) Proc. IX European Signal Processing Conf EUSIPCO '98, pp. 1665-1668Sun, H., Yang, J., Ren, M., A fast watershed algorithm based on chain code and its application in image segmentation (2005) Pattern Recognition Letters, 26 (9), pp. 1266-1274Osma-Ruiz, V., Godino-Llorente, J.I., Sáenz-Lechón, N., Gómez-Vilda, P., An improved watershed algorithm based on efficient computation of shortest paths (2007) Pattern Recognition, 40 (3), pp. 1078-1090Cousty, J., Bertrand, G., Najman, L., Couprie, M., Watershed cuts: Minimum spanning forests and the drop of water principle (2009) IEEE Transactions on Pattern Analysis and Machine Intelligence, 31 (8), pp. 1362-1374Roerdink, J.B.T.M., Meijster, A., The watershed transform: Definitions, algorithms and parallelization strategies (2000) Fundam. Inf, 41 (1-2), pp. 187-228Bieniek, A., Burkhardt, H., Marschner, H., Nölle, M., Schreiber, G., A parallel watershed algorithm (1997) Proceedings of 10th Scandinavian Conference on Image Analysis (SCIA97), pp. 237-244R. Audigier, R. de A. Lotufo, and M. Couprie, The tie-zone watershed: Definition, algorithm and applications, in In Proceedings of IEEE International Conference on Image Processing (ICIP'05), 2, 2005, pp. 654-657Audigier, R., Lotufo, R., Uniquely-determined thinning of the tie-zone watershed based on label frequency (2007) J. Math. Imaging Vis, 27 (2), pp. 157-173Berge, C., (1964) The Theory of graphs and its applications, , WileyMortensen, E.N., Barrett, W.A., Toboggan-based intelligent scissors with a four-parameter edge model (1999) Computer Vision and Pattern Recognition, IEEE Computer Society Conference on, 2, p. 2452Cousty, J., Bertrand, G., Najman, L., Couprie, M., Watershed cuts: Thinnings, shortest-path forests and topological watersheds (2009) IEEE Transactions on Pattern Analysis and Machine Intelligence, , to appearde Alencar Lotufo, R., Falcão, A.X., Zampirolli, F.A., Ift-watershed from gray-scale marker (2002) SIBGRAPI '02: Proceedings of the 15th Brazilian Symposium on Computer Graphics and Image Processing, pp. 146-152. , Washington, DC, USA: IEEE Computer Societ