In the past few years, immense improvement was obtained in the field of content-based image retrieval (CBIR). Nevertheless, existing systems still fail when applied to medical image databases. Simple feature-extraction algorithms that operate on the entire image for characterization of color, texture, or shape cannot be related to the descriptive semantics of medical knowledge that is extracted...

This work presents a novel hardware/software codesign approach to blob detection. Camera images are preprocessed on a field-programmable gate array that separates foreground pixels from the background. The foreground pixels are transferred to the PC over a 100 Mbit/s Ethernet interface by using a custom protocol. The PC reconstructs the images from received foreground pixels and extracts center...

Texture is an important part of the visual world of animals and men and their visual systems successfully detect, discriminate and segment texture. Relatively recently progress was made concerning structures in the brain which are presumably responsible for texture processing. Von der Heydt et al. (von der Heydt et al. 1992) reported on the discovery of a texture processing neuron in areas V1 a...

The Logarithmic Image Processing model (LIP) is a robust mathematical framework for the processing of transmitted and reflected images. It follows many visual, physical and psychophysical laws. This works presents a new formulation of a 2D–convolution of separable kernels using the LIP paradigm. A previously stated LIP–Sobel edge detector is redefined with the new proposed formulation, and the ...

Foreground blobs in a mixed stereo pair of videos (visible and infrared sensors) allow a coarse evaluation of the distances between each blob and the uncalibrated cameras. The main goals of this work are to find common feature points in each type of image and to create pairs of corresponding points in order to obtain coarse positionning of blobs in space. Feature points are found by two methods...

Conventional video surveillance systems often have several shortcomings. First, target detection can’t be accurate under the light variation environment or clustering backgrounds. Second, multiple targets tracking become difficult on a crowd scene because the split/merge and occlusions among the tracked targets occur frequently and irregularly. Third, it is difficult to the partition the tracke...

This paper describes a new approach for tracking circular traffic signs from image sequences. As a part of traffic sign recognition system, the traffic sign tracking will improve the performance of the recognition. By tracking the signs, search space is reduced and misdetection caused by temporal occlusion could be avoided. We propose a new blob tracking called two-layer blob tracking to track ...

The content of an image can be summarized by a set of homogeneous regions in an appropriate feature space. When exact shape is not important, the regions can be represented by simple “blobs”. Even for similar images, the blob representation of the two images might vary in shape, position, the number of blobs, and the represented features. In addition, separate blobs in one image might correspon...

With increased digital images in image repositories efficient indexing and searching becomes essential for large image archives. Content based image retrieval system (CBIR) retrieve relevant images using low-level features like color, texture and shape for image representation. In this approach, a scheme of novel color image retrieval based on visual interest point is presented. The existing sy...

We describe a method for estimation of 3-D geometry from 2-D blob features. Blob features are clusters of similar pixels in the image plane and can arise from similarity of color, texture, motion and other signal-based metrics. The motivation for considering such features comes from recent successes in real-time extraction and tracking of such blob features in complex cluttered scenes in which ...