Abstract   In this paper, we propose a new method for kernel based object tracking which tracks the complete non rigid object. Definition the union image blob and mapping it to a new representation which we named as potential pixels matrix are the main part of tracking algorithm. The union image blob is constructed by expanding the previous object region based on the histogram feature. The pote...

In this paper, a novel saliency theory based RR-IQA metric is introduced. As the human visual system is sensitive to the salient region, evaluating the image quality based on the salient region could increase the accuracy of the algorithm. In order to extract the salient regions, we use blob decomposition (BD) tool as a texture component descriptor. A new method for blob decomposition is propos...

abstract currently in iran, some manual methods are used for measuring spray droplet size which is very laborious and time consuming. in this paper, a software is presented based on image processing techniques, which is suitable for small object detection purpose that can be used in blob analysis of sprayer calibration and other similar applications. the algorithms have been implemented and ada...

Feature detection is very important to image processing area. In this paper we compare and analyze some characteristics of image processing algorithms for corner and blob feature detection. We also analyze the simulation results through image matching process. We show that how these algorithms work and how fast they execute. The simulation results are shown for helping us to select an algorithm...

We present a novel approach to interest-point detection tailored to range images. A range image is represented by two images with blob-like patterns that have easily detectable peaks and can be efficiently extracted using convolution kernels. These kernels were designed to produce repeatable and independent blob-like patterns when convolved with the range image. The interest-points correspond t...

The blob detection methods plays the vital role in the various image processing models. The blob detection models are utilized for the localization of the visible objects in the given images in order to understand the type and size of the objects. The blob detection can be utilized for the classification, categorization and other purposes in the image processing models. In the proposed model, t...

(b) (c) (d) (e) (f) (g) (h) Figure 6. Edge, texture, and shape features: (a) edges extracted from image 5a; (b) edges extracted from image 5b; (c) simple texture measure applied to image 5b; (d) thresholded texture measure yields a blob corresponding to the ordnance ; (e) left image of a stereo pair of the totally exposed ordnance; (f) range image from the stereo pair; (g) elevation map from th...

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...

In this paper, a new approach to real-time people segmentation through processing images captured by an infrared camera is introduced. The approach starts detecting human candidate blobs processed through traditional image thresholding techniques. Afterwards, the blobs are refined with the objective of validating the content of each blob. The question to be solved is if each blob contains one s...

In this paper, a new approach to real-time people segmentation through processing images captured by an infrared camera is introduced. The approach starts detecting human candidate blobs processed through traditional image thresholding techniques. Afterwards, the blobs are refined with the objective of validating the content of each blob. The question to be solved is if each blob contains one s...