Learn More
Multicolor fluorescence in situ hybridization (M-FISH) techniques provide color karyotyping that allows simultaneous analysis of numerical and structural abnormalities of whole human chromosomes. Chromosomes are stained combinatorially in M-FISH. By analyzing the intensity combinations of each pixel, all chromosome pixels in an image are classified. Often,(More)
Interest in face recognition systems has increased significantly due to the emergence of significant commercial opportunities in surveillance and security applications. In this paper we propose a novel technique to extract features from 3D face representations. In this technique, first the nose tip is automatically located on the range image, then the range(More)
This paper presents a new pattern matching method for fiducial mark alignment in a fuzzy space. The membership functions of fuzzy sets are designed by distance transforms, and their levels are set in the fuzzy space for fast matching of a specific fiducial mark. After the fuzzification, a sub-pixel level translation is estimated by a fuzzy similarity(More)
Multicolor fluorescence in-situ hybridization (m-fish) technique provides color karyotyping that allows simultaneous analysis of numerical and structural abnormalities of whole human chromosomes. Currently available m-fish systems exhibit misclassifications of multiple pixel regions that are often larger than the actual chromosomal rearrangement. This paper(More)
Automatic segmentation and classification of M-FISH chromosome images are jointly performed using a six-feature, 25-class maximum-likelihood classifier. Preprocessing of the images including background correction and six-channel color compensation method are introduced. A feature transformation method, spherical coordinate transformation, is introduced.(More)
Multicolor fluorescence in situ hybridization (M-FISH) techniques provide color karyotyping that allows simultaneous analysis of numerical and structural abnormalities of whole human chromosomes. Chromosomes are stained combinatorially in M-FISH. By analyzing the intensity combinations of each pixel, all chromosome pixels in an image are classified. Due to(More)
Since the birth of chromosome analysis by the aid of computers, building a fully automated chromosome analysis system has been the ultimate goal. Along with many other challenges, automating chromosome classification and segmentation has been one of the major challenges especially due to overlapping and touching chromosomes. In this paper we present a novel(More)
We introduce a novel multimodal framework for face recognition based on local attributes calculated from range and portrait image pairs. Gabor coefficients are computed at automatically detected landmark locations and combined with powerful anthropometric features defined in the form of geodesic and Euclidean distances between pairs of fiducial points. We(More)
In this paper, we present a novel identity verification system based on Gabor features extracted from range (3D) representations of faces. Multiple landmarks (fiducials) on a face are automatically detected using these Gabor features. Once the landmarks are identified, the Gabor features on all fiducials of a face are concatenated to form a feature vector(More)
Imaging specimens thicker than the depth-of-field of a microscope produces poor quality images as only a portion of the specimen is in focus. Therefore, even in the best focused image , there are always objects that are out of focus and thus blurred. It is difficult to accurately measure the size, shape, and boundary of a blurred object. As a result,(More)