Luis Garrido

Binary partition tree as an efficient representation for image processing, segmentation, and information retrieval

This paper discusses the interest of binary partition trees as a region-oriented image representation. Binary partition trees concentrate in a compact and structured representation a set of meaningful regions that can be extracted from an image. They offer a multiscale representation of the image and define a translation invariant 2-connectivity rule among regions. As shown in this paper, this representation can be used for a large number of processing goals such as filtering, segmentation, information retrieval and visual browsing. Furthermore, the processing of the tree representation leads to very efficient algorithms. Finally, for some applications, it may be interesting to compute the binary partition tree once and to store it for subsequent use for various applications. In this context, the paper shows that the amount of bits necessary to encode a binary partition tree remains moderate.

Antiextensive connected operators for image and sequence processing

This paper deals with a class of morphological operators called connected operators. These operators filter the signal by merging its flat zones. As a result, they do not create any new contours and are very attractive for filtering tasks where the contour information has to be preserved. This paper shows that connected operators work implicitly on a structured representation of the image made of flat zones. The max-tree is proposed as a suitable and efficient structure to deal with the processing steps involved in antiextensive connected operators. A formal definition of the various processing steps involved in the operator is proposed and, as a result, several lines of generalization are developed. First, the notion of connectivity and its definition are analyzed. Several modifications of the traditional approach are presented. They lead to connected operators that are able to deal with texture. They also allow the definition of connected operators with less leakage than the classical ones. Second, a set of simplification criteria are proposed and discussed. They lead to simplicity-, entropy-, and motion-oriented operators. The problem of using a nonincreasing criterion is analyzed. Its solution is formulated as an optimization problem that can be very efficiently solved by a Viterbi algorithm. Finally, several implementation issues are discussed showing that these operators can be very efficiently implemented.

Binary partition tree as an efficient representation for filtering, segmentation and information retrieval

This paper discusses the interest of binary partition trees as shape-oriented image representations. Binary partition trees concentrate in a compact and structured representation a set of meaningful regions that can be extracted from an image. This representation can be used for a large number of processing goals such as filtering, segmentation, information retrieval and visual browsing. Furthermore, the processing of the tree representation leads to very efficient algorithms.

Extensive operators in partition lattices for image sequence analysis

This paper deals with the class of extensive operators in the lattice of partitions. These operators are merging techniques. They can be used as filtering tools or as segmentation algorithms. In the first case, they are known as connected operators and, in the second case, they are region growing techniques. This paper discusses the basic elements that have to be defined to create a merging algorithm: merging order, merging criterion and region model. This analysis highlights the similarity and differences between a filtering tool, such as a connected operator, and a segmentation algorithm. Taking benefit from the filtering and segmentation viewpoints, we propose a general merging algorithm that can be used to create new connected operators (in particular self-dual operators) and efficient segmentation algorithms (robust criteria and efficient implementation).

Motion analysis of image sequences using connected operators

This paper deals with a class of morphological operators called connected operators. These operators interact with the signal by merging flat zones. As a results, they do not create any new contours and are very attractive for filtering tasks where the contour information has to be preserved. This paper focuses on a class of operators dealing with motion information. They remove from the original sequence the components that do not undergo a specific motion. They have a large number of applications including image sequence analysis with motion multiresolution decomposition and motion estimation.

Representing and retrieving regions using binary partition trees

This paper discusses the interest of Binary Partition Trees for image and region representation in the context of indexing and similarity based retrieval. Binary Partition Trees concentrate in a compact and structured way the set of regions that compose an image. Since the tree is able to represent images in a multiresolution way, only simple descriptors need to be attached to the nodes. Moreover, this representation is used for similarity based region retrieval.

Connected Operators Based on Region-Tree Pruning

This paper discusses region-based representations useful to create connected operators. The filtering approach involves three steps: first, a region tree representation of the input image is constructed. Second, the simplification is obtained by pruning the tree and third, and output image is constructed from the pruned tree. The paper focuses in particular on several pruning strategies that can be used on tree representation.

Visual segment tree creation for MPEG-7 description schemes

The paper deals with the creation of visual segment trees involved in MPEG-7 description schemes. After a brief overview of MPEG-7 description schemes in general and of the Segment Description Scheme in particular, tools allowing the creation of segment trees are discussed. It is proposed to create a binary partition tree in a first step and to restructure the tree in a second step. Several examples involving spatial and temporal partition trees are presented.

Connected operators based on region-tree pruning strategies

This paper discusses region-based representations useful to create connected operators. The filtering approach involves three steps: 1) a region tree representation of the input image is constructed; 2) the simplification is obtained by pruning the tree; and 3) and output image is constructed from the pruned tree. The paper focuses in particular on the pruning strategies that can be used depending of the increasing of the simplification criteria.

Stereo image analysis using connected operators

Connected operators are increasingly used in image processing due to their properties of simplifying the image with various criteria, without loosing contours information. These properties are related to the connected operator approach that either preserves or completely eliminates a determined connected component, according to an established criterion of analysis. In this paper we will define a new connected operator for stereo images. The goal is to simplify one of the images (left) in the sense that the operator will eliminate the image components that are not present at a determined location in the other image (right). This filter let us select in a stereo image, objects as a function of their distance from the observer (for instance used in auto guided vehicles).Connected operators are increasingly used in image processing due to their properties of simplifying the image with various criteria, without loosing contours information. These properties are related to the connected operator approach that either preserves or completely eliminates a determined connected component, according to an established criterion of analysis. In this paper we will define a new connected operator for stereo images. The goal is to simplify one of the images (left) in the sense that the operator will eliminate the image components that are not present at a determined location in the other image (right). This filter let us select in a stereo image, objects as a function of their distance from the observer (for instance used in auto guided vehicles).Connected operators are increasingly used in image processing due to their properties of simplifying the image with various criteria, without loosing contours information. These properties are related to the connected operator approach that either preserves or completely eliminates a determined connected component, according to an established criterion of analysis. In this paper we will define a new connected operator for stereo images. The goal is to simplify one of the images (left) in the sense that the operator will eliminate the image components that are not present at a determined location in the other image (right). This filter let us select in a stereo image, objects as a function of their distance from the observer (for instance used in auto guided vehicles).