Ick Hoon Jang

Learn More
In this paper, we propose a content-based image retrieval method based on an efficient combination of multiresolution color and texture features. As its color features, color autocorrelograms of the hue and saturation component images in HSV color space are used. As its texture features, BDIP and BVLC moments of the value component image are adopted. The(More)
In this paper, we present an improved image formation model and propose a color image enhancement using single-scale retinex based on the model. In the presented image formation model, an input image is represented as the product of global illumination, local illumination, and reflectance. In the proposed color image enhancement, an input RGB color image is(More)
Content Based Image Retrieval (CBIR) is a process to retrieve a stored image from database by supplying an image as query instead of text. This can be done by proper feature extraction and querying process. The features like histogram, color values and edge detection plays very vital role in proper image retrieval. Here we have implemented a method of image(More)
A 30-yr-old man was referred for suspicious rectal cancer because of ulcerated lesions in the rectum and a palpable mass in left inguinal area. Sigmoidoscopy showed two indurated masses and histologic evaluation of biopsy revealed obliterative endarteritis with heavy plasma cell infiltration. Both venereal disease research laboratories (VDRL) and(More)
In this paper, we propose a texture feature-based language identification using wavelet-domain BDIP (block difference of inverse probabilities), BVLC (block variance of local correlation coefficients), and NRMA (normalized magnitude) features. The proposed method includes three special operations of NRMA, Donoho's soft-thresholding, and variance(More)