• Title/Summary/Keyword: gray scale image

Search Result 256, Processing Time 0.028 seconds

Fast Text Line Segmentation Model Based on DCT for Color Image (컬러 영상 위에서 DCT 기반의 빠른 문자 열 구간 분리 모델)

  • Shin, Hyun-Kyung
    • The KIPS Transactions:PartD
    • /
    • v.17D no.6
    • /
    • pp.463-470
    • /
    • 2010
  • We presented a very fast and robust method of text line segmentation based on the DCT blocks of color image without decompression and binary transformation processes. Using DC and another three primary AC coefficients from block DCT we created a gray-scale image having reduced size by 8x8. In order to detect and locate white strips between text lines we analyzed horizontal and vertical projection profiles of the image and we applied a direct markov model to recover the missing white strips by estimating hidden periodicity. We presented performance results. The results showed that our method was 40 - 100 times faster than traditional method.

Security Algorithm for Vehicle Type Recognition (에지영상의 비율을 이용한 차종 인식 보안 알고리즘)

  • Rhee, Eugene
    • Journal of Convergence for Information Technology
    • /
    • v.7 no.2
    • /
    • pp.77-82
    • /
    • 2017
  • In this paper, a new security algorithm to recognize the type of the vehicle with the vehicle image as a input image is suggested. The vehicle recognition security algorithm is composed of five core parts, such as the input image, background removal, edge areas extraction, pre-processing(binarization), and the vehicle recognition. Therefore, the final recognition rate of the security algorithm for vehicle type recognition can be affected by the function and efficiency of each step. After inputting image into a gray scale image and removing backgrounds, the binarization is performed by extracting only the edge region. After the pre-treatment process for making outlines clear, the type of vehicles is categorized into large vehicles, passenger cars and motorcycles through the ratio of height and width of the vehicle.

A Study on the Face Image to Color of Make-up (색채 메이크업에 의한 얼굴이미지 연구)

  • Song, Mi-Young;Park, Oak-Reon;Ha, Jong-Kyung
    • Fashion & Textile Research Journal
    • /
    • v.7 no.5
    • /
    • pp.527-534
    • /
    • 2005
  • The purpose of this research is to study face images according to color of make-up was made by computer graphic simulation. The various facial images can be helpful for choosing suitable make-up color planning. In order to find out the differences of face images by make-up color, three different foundations and seven eye-shadows, six lips were applied on the round face model. Make-up Image Scale was used the scale of seven point modified the S-D method. Data were analyzed by Varimax perpendicular rotation method, Duncan's Multiple Range Test, Three-way ANOVA. As the result of make-up image perception analysis, a factor structure was divided into mildness, modernness, elegance, unique. The factor of mildness, modernness, unique affected on the foundation color. Foundation color was found out to be influential variable to distinguish color perception abilities. Also, the foundation, eye-shadow, lip color were influenced interactively on the perception of elegance factor. Pink color was important color, influenced on the mildness factor. Gray and purple color were influenced on the modernness factor. Mildness factor was perceived as the most bright foundation but unique factor was perceived as the most dark foundation. Then, the foundation, eye-shadow, lip color were influenced interactively on the perception of facial images. The results can be effectively applied to today's marketing and color design management which is focused on the product's emotional image in customer's mind.

Visualized Malware Classification Based-on Convolutional Neural Network (Convolutional Neural Network 기반의 악성코드 이미지화를 통한 패밀리 분류)

  • Seok, Seonhee;Kim, Howon
    • Journal of the Korea Institute of Information Security & Cryptology
    • /
    • v.26 no.1
    • /
    • pp.197-208
    • /
    • 2016
  • In this paper, we propose a method based on a convolutional neural network which is one of the deep neural network. So, we convert a malware code to malware image and train the convolutional neural network. In experiment with classify 9-families, the proposed method records a 96.2%, 98.7% of top-1, 2 error rate. And our model can classify 27 families with 82.9%, 89% of top-1,2 error rate.

A Novel Method to Evaluate the Emotional Image Quality with CIECAM02

  • Chong, Jong-Ho;Lee, Seung-Bae;Park, Hye-Ryoung;Kim, Sang-Ho;Bae, Jae-Woo;Kim, Hye-Dong;Kim, Hun-Soo
    • 한국정보디스플레이학회:학술대회논문집
    • /
    • 2008.10a
    • /
    • pp.47-50
    • /
    • 2008
  • We propose a new method evaluating the image quality of display devices using the CIECAM02 that is the recently developed CIE color appearance model and provides an extension of the previously recommended CIE color spaces. We develop the evaluation method that quantifies the color reproduction capability, emotional gray scale (gradation), and visual perception contrast (perceptual contrast range) based on the gamut in this model.

  • PDF

Auto-Detection Algorithm of Gait's Joints According to Gait's Type (보행자 타입에 따른 보행자의 관절 점 자동 추출 알고리즘)

  • Kwak, Nae-Joung;Song, Teuk-Seob
    • Journal of Korea Multimedia Society
    • /
    • v.21 no.3
    • /
    • pp.333-341
    • /
    • 2018
  • In this paper, we propose an algorithm to automatically detect gait's joints. The proposed method classifies gait's types into front gait and flank gait so as to automatically detect gait's joints. And then according to classified types, the proposed applies joint extracting algorithm to input images. Firstly, we split input images into foreground image using difference images of Hue and gray-scale image of input and background one and extract gait's object. The proposed method classifies gaits into front gait and flank gait using ratio of Face's width to torso's width. Then classified gait's type, joints are detected 10 at front gait and detected 7~8 at flank gait. The proposed method is applied to the camera's input and the result shows that the proposed method automatically extracts joints.

Contrast Enhancement of Blurred Images Using Fuzzy Logic Concepts (퍼지 논리를 이용한 흐린 영상의 콘트라스트 향상)

  • 박중조;김경민;박귀태
    • Journal of the Korean Institute of Telematics and Electronics B
    • /
    • v.31B no.8
    • /
    • pp.181-191
    • /
    • 1994
  • A new method for enhancing blurred images using fuzzy logic concepts is proposed. Blurred images contain blurred boundaries which make it difficult to detect edges and segment areas in images. In order to sharpen blurred edges local contrast information of an image and erosion/dilation properties of local min/max operations are used in which local min/max operations are fuzzy logic operations. so that given images are transformed to fuzzy images and then these operations are applied on them. In this method the sharpening operation can be iteratively applied to the image to get better deblurring effect and gray-scale "salt-and-pepper" noises are suppressed. the efficiency of our algorithm is demonstrated through experimental results obtained with artificially-made blurred images and real blurred images.

  • PDF

Vertical Edge Based Algorithm for Korean License Plate Extraction and Recognition

  • Yu, Mei;Kim, Yong Deak
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.25 no.7A
    • /
    • pp.1076-1083
    • /
    • 2000
  • Vehicle license plate recognition identifies vehicle as a unique, and have many applications in traffic monitoring field. In this paper, a vertical edge based algorithm to extract license plate within input gray-scale image is proposed. A size-and-shape filter based on seed-filling algorithm is applied to remove the edges that are impossible to be the vertical edges of license plate. Then the remaining edges are matched with each other according to some restricted conditions so as to locate license plate in input image. After license plate is extracted. normalized and segmented, the characters on it are recognized by template matching method. Experimental results show that the proposed algorithm can deal with license plates in normal shape effectively, as well as the license plates that are out of shape due to the angle of view.

  • PDF

The viewing angle switching of TN-LCD with two tilted LC layer (기울어진 두 액정 층을 이용한 비틀린 네마틱 액정 셀의 시야각 조절)

  • Choi, Min-Oh;Lim, Young-Jin;Jeong, Eun;Lee, Seung-Hee
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
    • /
    • 2006.04a
    • /
    • pp.45-46
    • /
    • 2006
  • We have studied the viewing angle control using a twist nematic liquid crystal display (TN-LCDs). These TK-LCDs have the characteristics, of which is not good image quality, for examples low Contrast ratio and gray scale inversion problems at upper and down viewing direction. TN-LCDs have the function of switching between the wide viewing mode and narrow viewing angle mode using two tilted LC layers. Tilt angles of the two LC layers, $14^{\circ}$ and $60^{\circ}$ were required in both wide viewing angle and narrow viewing angle modes, respectively. Consequently, this device is compatible with two image performances of which the wide viewing angle mode and Narrow viewing angle mode.

  • PDF

Remote Sensing Information Models for Sediment and Soil

  • Ma, Ainai
    • Proceedings of the KSRS Conference
    • /
    • 2002.10a
    • /
    • pp.739-744
    • /
    • 2002
  • Recently we have discovered that sediments should be separated from lithosphere, and soil should be separated from biosphere, both sediment and soil will be mixed sediments-soil-sphere (Seso-sphere), which is using particulate mechanics to be solved. Erosion and sediment both are moving by particulate matter with water or wind. But ancient sediments will be erosion same to soil. Nowadays, real soil has already reduced much more. Many places have only remained sediments that have ploughed artificial farming layer. Thus it means sediments-soil-sphere. This paper discusses sediments-soil-sphere erosion modeling. In fact sediments-soil-sphere erosion is including water erosion, wind erosion, melt-water erosion, gravitational water erosion, and mixed erosion. We have established geographical remote sensing information modeling (RSIM) for different erosion that was using remote sensing digital images with geographical ground truth water stations and meteorological observatories data by remote sensing digital images processing and geographical information system (GIS). All of those RSIM will be a geographical multidimensional gray non-linear equation using mathematics equation (non-dimension analysis) and mathematics statistics. The mixed erosion equation is more complex that is a geographical polynomial gray non-linear equation that must use time-space fuzzy condition equations to be solved. RSIM is digital image modeling that has separated physical factors and geographical parameters. There are a lot of geographical analogous criterions that are non-dimensional factor groups. The geographical RSIM could be automatic to change them analogous criterions to be fixed difference scale maps. For example, if smaller scale maps (1:1000 000) that then will be one or two analogous criterions and if larger scale map (1:10 000) that then will be four or five analogous criterions. And the geographical parameters that are including coefficient and indexes will change too with images. The geographical RSIM has higher precision more than mathematics modeling even mathematical equation or mathematical statistics modeling.

  • PDF