Region-of-interest (ROI) detection plays an important role in filtering out pornographic images. Skin-color models, as a traditional approach, extract skin-color regions as ROI. However, the approach is difficult to differentiate between human skins and other objects with the skin-color. Furthermore, skin-color regions are always larger than the subareas containing pornographic parts. In this p...

In this paper we propose a method to detect human faces in color images , that uses a combination of color spaces and edge detection for segmentation. Algorithm ingeniously combines different color space models, specifically, HSI and YCbCr along with Canny and Prewitt edge detection techniques.Experimental results indicate improved false acceptance rates. The overall performance of the face det...

This paper addresses applied image segmentation techniques for the detection of dyed objects (transgenic barley cells) in microscope color images. It is shown on exemplary image data that edge detection with Canny’s algorithm applied to the hue channel of the HSV color space outperforms both multidimensional edge detection in RGB space as well as color-based pixel classification. This provides ...

Obstacle detection is a key component of autonomous systems. In particular, when dealing with large robots in unstructured environments, robust obstacle detection is vital. In this paper, we describe an obstacle detection methodology which combines two complimentary methods: adaptive color segmentation, and stereo-based color homography. This algorithm is particularly suited for environments in...

Recently, a lot of research has been done on the matching of images and their structures. Although the approaches are very different, most methods use some kind of point selection from which descriptors or a hierarchy are derived. We focus here on the methods that are related to the detection of points and regions that can be detected in an affine invariant way. Most of the previous research co...

This paper presents a trainable object detection architecture that is applied to detecting people in static images of cluttered scenes. This problem poses several challenges. People are highly non-rigid objects with a high degree of variability in size, shape, color, and texture. Unlike previous approaches, this system learns from examples and does not rely on any a priori (hand-crafted) models...

In this paper, we present a logo and trademark retrieval system for general, unconstrained, color image databases that extends the Color Edge Co-occurrence Histogram (CECH) object detection scheme. We introduce more accurate information to the CECH, by virtue of incorporating color edge detection using vector order statistics. This produces a more accurate representation of edges in images, in ...

Object detection and tracking have been studied separately in most cases. Particle filtering has proven very successful for non-linear and nonGaussian estimation problems. This paper presents a new method for tracking moving vehicles with temporal disappearance. The proposed method can continue tracking after disappearance. Color distribution of objects is integrated into particle filtering alg...

A novel approach for forest fire detection using image processing technique is proposed. A rule based color model for fire pixel classification is used. The proposed algorithm uses RGB and YCbCr color space. The advantage of using YCbCr color space is that it can separate the luminance from the chrominance more effectively than RGB color space. The performance of the proposed algorithm is teste...

Face detection is a very challenging and interesting problem. In this paper, a new scheme for detection of multiple faces using Haar wavelet packet decomposition based on quantized skin color region merging under unconstrained scene conditions is presented. Color clustering and filtering using approximations of the YCbCr and HSV skin color subspaces are applied on the original image by providin...