Abstract: An image enhancement method and system are provided. The image enhancement method and system are capable of improving image quality by performing gamma corrections on global and local illuminations and reflectance estimated from an input image, in consideration of dynamic range and contrast of the image, respectively. Particularly, in a case of a color image, the red, green, and blue (RGB) component images are converted into hue, saturation, and value (HSV) component images, and the global and local illuminations and reflectance estimated from the V component image. By converting the hue (H), saturation (S), and enhanced value (V) into RGB, an enhanced color image can be obtained.

Abstract: Disclosed is a device for binarizing an image. The device comprises an input part for receiving an image, a block classification part for dividing the received image into blocks, and classifying the divided blocks into character blocks and background blocks, an edge enhancement part for enhancing edges of a character block using relations between neighboring pixels in the character block classified by the block classification part, and generating a threshold for distinguishing character pixels and background pixels of the character block, and a binarization part for binarizing pixels of character blocks output from the edge enhancement part into a first brightness value for character pixels and a second brightness value for background pixels by comparing the pixels of the character blocks with the threshold, and binarizing pixels of background blocks output from the block classification part into the second brightness value.

Abstract: Disclosed is a device and method for recognizing characters in an image. An input part receives the image. A blurring decision part classifies the received image into character blocks and background blocks, calculates an average energy ratio of the character blocks, and compares the average energy ratio with a predetermined threshold to determine whether the received image is blurred. If the received image is not blurred, an image binarization part classifies the received image into character blocks and background blocks, compares pixels in the character blocks with a pixel threshold, binarizes the pixels in the character blocks into a brightness value for a character pixel and a brightness value for a background pixel based on the comparison, and binarizes pixels in the background blocks into the brightness value for a background pixel. A character recognition part recognizes characters in the binarized image.

Abstract: An image enhancement method and system are provided. The image enhancement method and system are capable of improving image quality by performing gamma corrections on global and local illuminations and reflectance estimated from an input image, in consideration of dynamic range and contrast of the image, respectively. Particularly, in a case of a color image, the red, green, and blue (RGB) component images are converted into hue, saturation, and value (HSV) component images, and the global and local illuminations and reflectance estimated from the V component image. By converting the hue (H), saturation (S), and enhanced value (V) into RGB, an enhanced color image can be obtained.

Abstract: A device and method for correcting a skew of an object in an image. The device and method comprises an input part for receiving an image; a binarization part for binarizing pixels of the image into pixels having brightness values for character pixels and background pixels; a candidate stripe generation part for generating candidate stripes by performing dilation on character regions of the binarized image. The device and method further comprises a stripe classification part for classifying candidate stripes having a predetermined eccentricity and blob size among the candidate stripes, as valid stripes; a skew angle decision part for calculating direction angles of the classified stripes, and determining a direction angle having the largest count value as a skew angle; and a skew correction part for correcting a skew of an image by rotating the mage by the skew angle.

Abstract: A device and method for determining whether or not an image is blurred. The device and method comprises an input part for receiving an image; a block classification part for dividing the received image into blocks and classifying the divided blocks into character blocks and background blocks; a character block energy calculation part for calculating an average energy ratio of the character blocks; and a blurring detection part for calculating an average energy ratio of the character blocks and determining whether or not the image is blurred based on a comparison of the average energy ratio with a predetermined threshold.

Abstract: Disclosed is a device for binarizing an image. The device comprises an input part for receiving an image, a block classification part for dividing the received image into blocks, and classifying the divided blocks into character blocks and background blocks, an edge enhancement part for enhancing edges of a character block using relations between neighboring pixels in the character block classified by the block classification part, and generating a threshold for distinguishing character pixels and background pixels of the character block, and a binarization part for binarizing pixels of character blocks output from the edge enhancement part into a first brightness value for character pixels and a second brightness value for background pixels by comparing the pixels of the character blocks with the threshold, and binarizing pixels of background blocks output from the block classification part into the second brightness value.

Abstract: A device and method for determining whether or not an image is blurred. The device and method comprises an input part for receiving an image; a block classification part for dividing the received image into blocks and classifying the divided blocks into character blocks and background blocks; a character block energy calculation part for calculating an average energy ratio of the character blocks; and a blurring detection part for calculating an average energy ratio of the character blocks and determining whether or not the image is blurred based on a comparison of the average energy ratio with a predetermined threshold.

Abstract: A device for extending a character region in an image comprising an input part for receiving an input image, a block classification part for classifying the input image into character blocks and background blocks, and converting pixels in the character blocks into pixels having a first brightness value and pixels in the background blocks into pixels having a second brightness value, and a position search part for searching for left, right, top and bottom positions of a character region by horizontally and vertically scanning the block-classified image, and determining a position of the character region. The device for extending a character region in an image further comprises a region of contents (ROC) extraction part for extracting an image in the determined position of the character region from the input image, and an ROC extension part for extending the extracted image of the character region to a size of the input image.

Abstract: Disclosed is a device and method for recognizing characters in an image. An input part receives the image. A blurring decision part classifies the received image into character blocks and background blocks, calculates an average energy ratio of the character blocks, and compares the average energy ratio with a predetermined threshold to determine whether the received image is blurred. If the received image is not blurred, an image binarization part classifies the received image into character blocks and background blocks, compares pixels in the character blocks with a pixel threshold, binarizes the pixels in the character blocks into a brightness value for a character pixel and a brightness value for a background pixel based on the comparison, and binarizes pixels in the background blocks into the brightness value for a background pixel. A character recognition part recognizes characters in the binarized image.

Abstract: A device and method for correcting a skew of an object in an image. The device and method comprises an input part for receiving an image; a binarization part for binarizing pixels of the image into pixels having brightness values for character pixels and background pixels; a candidate stripe generation part for generating candidate stripes by performing dilation on character regions of the binarized image. The device and method further comprises a stripe classification part for classifying candidate stripes having a predetermined eccentricity and blob size among the candidate stripes, as valid stripes; a skew angle decision part for calculating direction angles of the classified stripes, and determining a direction angle having the largest count value as a skew angle; and a skew correction part for correcting a skew of an image by rotating the mage by the skew angle.