We present a method for segmenting 2D microscopy images of freshwater green microalgae. Our approach is based on a specialized level set method, leading to efficient and highly accurate algae segmentation. the level s...
详细信息
We present a method for segmenting 2D microscopy images of freshwater green microalgae. Our approach is based on a specialized level set method, leading to efficient and highly accurate algae segmentation. the level set formulation of our problem allows us to generate an algae's boundary curve as the result of an evolving level curve, based on computed background and algae regions in a given image. By characterizing the distributions of image intensity values in local regions, we are able to automatically classify image regions into background and algae regions. We present results obtained with our method. these results are very promising as they document that we can achieve highly accurate algae segmentations when comparing ours against manually segmented images (segmented by an expert biologist) and with results derived by other approaches covered in the literature.
Deaf people use systems of communication based on sign language and finger spelling. Finger spelling is a system where each letter of the alphabet is represented by a unique and discrete movement of the hand. RGB and ...
详细信息
Deaf people use systems of communication based on sign language and finger spelling. Finger spelling is a system where each letter of the alphabet is represented by a unique and discrete movement of the hand. RGB and depthimages can be used to characterize hand shapes corresponding to letters of the alphabet. there exists an advantage of depth sensors, as Kinect, over color cameras for finger spelling recognition: depthimages provide 3D information of the hand. In this paper, we propose a model for finger spelling recognition based on depth information using kernel descriptors, consisting of four stages. the performance of this approach is evaluated on a dataset of real images of the American Sign Language finger spelling. Different experiments were performed using a combination of both descriptors over depth information. Our approach obtains 92.92% of mean accuracy with 50% of samples for training, outperforming other state-of-the-art methods.
Emergency events involving fire are potentially harmful, demanding a fast and precise decision making. the use of crowd sourcing image and videos on crisis management systems can aid in these situations by providing m...
详细信息
Emergency events involving fire are potentially harmful, demanding a fast and precise decision making. the use of crowd sourcing image and videos on crisis management systems can aid in these situations by providing more information than verbal/textual descriptions. Due to the usual high volume of data, automatic solutions need to discard non-relevant content without losing relevant information. there are several methods for fire detection on video using color-based models. However, they are not adequate for still image processing, because they can suffer on high false-positive results. these methods also suffer from parameters with little physical meaning, which makes fine tuning a difficult task. In this context, we propose a novel fire detection method for still imagesthat uses classification based on color features combined with texture classification on super pixel regions. Our method uses a reduced number of parameters if compared to previous works, easing the process of fine tuning the method. Results show the effectiveness of our method of reducing false-positives while its precision remains compatible withthe state-of-the-art methods.
this special issue of Journal of Mathematical Imaging and Vision contains expanded versions of papers presented at sibgrapi 2011, the 24thconference on graphics, patterns, and images. sibgrapi is the most traditional...
详细信息
this special issue of Journal of Mathematical Imaging and Vision contains expanded versions of papers presented at sibgrapi 2011, the 24thconference on graphics, patterns, and images. sibgrapi is the most traditional meeting in Latin America on Computer graphics, Image Processing, Pattern Recognition and Computer Vision.
We present two new methods for creating stereoscopic models displayed over horizontal screens based on image processing. Both methods use Computer Vision: the first is constructed by the modification of the Harley'...
详细信息
ISBN:
(纸本)9781728106045
We present two new methods for creating stereoscopic models displayed over horizontal screens based on image processing. Both methods use Computer Vision: the first is constructed by the modification of the Harley's rectification algorithm, and the second uses the Fundamental theorem of Projective Geometry. Different from the solutions available in the literature, we do not use a calibration pattern, and we do not use unconstrained nonlinear optimization, resulting in simple and efficient algorithms.
暂无评论