Inspired on the techniques used by painters to overlap layers of various hues of paint to create oil paintings, and also on observations of the the arrangement of Short-(S), Middle-(M), and Long-(L) wavelength-sensitive cones of the human retina for the interpretation of the colors, this paper proposes the use of the new color space called HSM to the processing of color images. To demonstrate t...

Cytochrome oxidase (CO) dense blobs in primate striate cortex provide a striking example of parallel processing of visual information. The level of isolation of the blobs from the surrounding interblob tissue was investigated in the present study by combining CO staining with Golgi impregnation of dendritic arbors in the same tissue sections. The data are based on material from two marmoset and...

Edge detection is a very essential part of image processing, as quality and accuracy of detection determines the success of further processing. We have developed a new self learning technique for edge detection using dictionary comprised of eigenfilters constructed using features of the input image. The dictionary based method eliminates the need of pre or post processing of the image and accou...

The goal of this project is to monitor activities at traffic intersections for detecting/predicting situations that may lead to accidents. Some of the key elements for robust intersection monitoring are camera calibration, motion tracking, incident detection, etc. In this paper, we consider the motion-tracking problem. A multi-level tracking approach using Kalman filter is presented for trackin...

This research work is extended version of our previous work, which was carried out on 2-D image edge detection using daubachies db10 wavelet transform. Here in this paper, the db10 wavelet transform for edge detection is compared with most widely used edge detection techniques, such as Sobel, Prewitt, Roberts and Laplacian of Gaussian (LoG) and Canny. The comprehensive studies along with pros a...

In this paper, we propose a new approach in image processing for interest point detection. Thanks to the link between linear scalespace and wavelet decompositions, we are able to build a structure in scale-space based on wavelet maxima lines. This framework allows robust detection of objects (or blob-like structures) present in the image, and the computation of their characteristic scale. Event...

1077-3142/$ see front matter 2011 Elsevier Inc. A doi:10.1016/j.cviu.2011.12.002 ⇑ Corresponding author. E-mail addresses: [email protected] (L. Ferraz Binefa). Usually, state-of-the-art interest point detectors tend to over-represent the local image structures associating several interest points for each local image structure. This fact avoids interest points to clearly stand out against its...

Biomedical data, such as MRI, MEG, EEG or optical imaging data, present a challenge to any data processing software. Feature point detection has many parameters such as edge detection, corner detection and blob detection (region of interest). Compression technique is used to reduce the size of image over selected region over medical image. So that it will helpful to transfer over WLAN. This pap...

This article proposes a new method to evaluate basic characteristics of the dynamics of a coherent plasma structure (blob). With this method, one can evaluate the propagation angle of a blob in a two-dimensional plasma cross section as well as the blob velocity, size, and amplitude from one-dimensional data. The method is applied to blob measurements from the Lithium beam emission spectroscopy ...

This paper proposes a novel nonlinear filter, named rank order Laplacian of Gaussian (ROLG) filter, based on which a new interest point detector is developed. The ROLG filter is a weighted rank order filter. It is used to detect the image local structures where a significant majority of pixels are brighter or darker than a significant majority of pixels in their corresponding surroundings. Comp...