• Journal of the Korea Society of Computer and Information
• /
• v.28 no.8
• /
• pp.77-86
• /
• 2023

The background of this study lies in the increasing economic value of Korean fonts and the necessity for font development focused on small character design suitable for the mobile environment. The objective of this study is to analyze and propose strategies to improve readability on mobile screens. The research was conducted by applying eight attributes that could enhance readability according to Tim Ahrens to the design process of a Korean mobile font, adjusting Google's Noto Sans Korean for print/publishing and for small sizes. The results of the study indicate that 1. type width should be increased, 2. open counter (interior space) should be increased, 3. closed counter should be decreased, 4. font weight should be increased, 5. stroke contrast should be decreased, 6. spacing between characters should be increased. Therefore, distinct font families should be provided, differentiating between print/publishing and mobile use, as well as varying font weights and sizes, applying readability and legibility enhancement techniques for Korean fonts.

• Journal of the Korean Graphic Arts Communication Society
• /
• v.19 no.1
• /
• pp.55-63
• /
• 2001

Visual and color in Korean newspaper advertisements appeared in transformational advertising (21cm$\times$30.4cm) were analyzed. Data were gathered from 191 advertisements shown on major four daily newspaper; Dong-a, Joong-ang, Chosun, and Hanguk from October to December in 2000. From the results of this research, researcher concluded the followings; Both Korean and English are frequently used. With expectation of high readability, Roman/serifs and San serifs are mostly used typefaces. Selecting color for copy and backgraund in advertisements became more varied to satisfy varied consumers' personality.

• Journal of KIISE:Software and Applications
• /
• v.31 no.1
• /
• pp.8-19
• /
• 2004

In this paper, we propose an efficient method for locating destination address block on both of machine-Printed and handwritten Korean mail piece images. The proposed method extracts connected components from the binary mail piece image, generates text lines by merging them, and then groups the text fines into nine clusters. The destination address block is determined by selecting some clusters. Considering the geometric characteristics of address information on Korean mail piece, we split a mail piece image into nine areas with an equal size. The nine clusters are initialized with the center coordinate of each area. A modified Manhattan distance function is used to compute the distance between text lines and clusters. We modified the distance function on which the aspect ratio of mail piece could be reflected. The experiment done with live Korean mail piece images has demonstrated the superiority of the Proposed method. The success rate for 1, 988 testing images was about 93.56%.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.19 no.11
• /
• pp.2276-2290
• /
• 1994

In this paper, we propose an algorithm for character recognition using the subdivided type and the stable structure information. The subdivided type of character is acquired from the stable structure information of character which is extracted from an input character. Firstly, the character is obtained from a scanner and classified into on of 6 types by using directional density vector. And then, the stable structure information is extracted from each character and the character is subdivided into on of 26 types. Finally, the classified character is recognized by using neural network which is inputted the directional density vector equivalent to JASO area or recognized direct. Aa a result of experiment with KS C 5601 2350 printed Hangeul characters, we obtain the recognition rate of 94%.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.14 no.5
• /
• pp.15-21
• /
• 1977

The syntactic pattern recognition system of Korean characters is composed of three main functional parts; Preprocessing, Graph-representation, and Segmentation. In preprocessing routine, the input pattern has been thinned using the Hilditch's thinning algorithm. The graph-representation is the detection of a number of nodes over the input pattern and codification of branches between nodes by 8 directional components. Next, segmentation routine which has been implemented by top down nondeterministic parsing under the control of tree grammar identifies parts of the graph-represented Pattern as basic components of Korean characters. The authors have made sure that this system is effective for recognizing Korean characters through the recognition simulations by digital computer.

• Archives of design research
• /
• v.14
• /
• pp.321-333
• /
• 1996

The typeface of the Shhnch 'ongjon woodblocks is unsophisticated and old-fashioned while at the same time having a tidiness and strength that give it its special appeal. This is the typeface used in publishing novPls for sale to the common people during the latter half of the Choson Dynasty_ Their demands could not be satisfied with most currently available literature. which was intended to suit the tastes of the official class. As a result of a development to overcome the unbalanced use of space characteristic of letterforms that followed the geometric principles of early Hangul. the typeface followed the refined. feminine "hrushstroke" style of kungch 'e. establishing itself as a "rough" face displaying the characteristics of carved. woodblock printing in answer to the needs of the common p-eople who had the greatest need of Hangul during the time of its f1owering. The Shhnch 'ongjon face is characterized by thin horizontal strokes. thick vertical strokes. and the appearance of being condensed left to right. They possess simple yet varied form. With these characteristics the Shimch' ongjon typeface. if revived and compared to other typefaces. has a beauty of structure and composition and a unique. modern lmage with excellent readability. giving it great significance for modern r langul typography.r langul typography.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.12 no.4
• /
• pp.306-310
• /
• 2002

In this paper, we realized a system that converts the Korean alphabet (Hangul) images, which are in any domain that is formed by the finger movement on the Hangul document, to the editable characters and then outputs them to the word editor. The domain of hand is separated from the sphere of document in the pre-process step of image. The centroid point of hand is drawn by the maximum circular movement method. After the system recognizes the hand with the circular pattern vector algorithm, finds out the position of finger by the distance spectrum and then draws out the sphere of selected character image by the finger movement to divide the characters into character units by applying the histogram between the Hangul characters. We standardized the characters of various sizes. We used the circular pattern vector algorithm that grafts on the fuzzy inference to divert the character images of the domain, which user wants, to the editable characters by comparing the characteristic vectors between the standard pattern character and the inputted character and by recognizing the character.

• Journal of Korean Institute of Industrial Engineers
• /
• v.17 no.2
• /
• pp.27-37
• /
• 1991

A recognition algorithm for Hangul is developed by structural analysis to Hangul in this theses. Four major procedures are proposed : preprocessing, type classification, separation of consonant and vowel, recognition. In the preprocessing procedure, the thinning algorithm proposed by CHEN & HSU is applied. In the type classification procedure, thinned Hangul image is classified into one of six formal types. In the separation of consonant and vowel procedure, starting from branch-points which are existed in a vowel, character elements are separated by means of tracing branch-point pixel by pixel and comparison with proposed templates. In the same time, the vowels are recognized. In the recognition procedure, consonants are extracted from the separated Hangul character and recognized by modified Crossing method. Recognized characters are converted into KS-5601-1989 codes. The experiments show that correct recognition rate is about 80%-90% and recognition speed is about 2-3 character persecond in three types of different input data on computer with 80386 microprocessor.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.19 no.11
• /
• pp.2133-2146
• /
• 1994

In this paper, we present a method for dynamic Jaso segmentation and Hangeul recognition using neural network. It uses the feature vector which is extracted from the mesh depending on the segmentation result. At first, each character is converted to 256 dimension feature vector by four direction contributivity and $8\times8$ mesh. And then, the character is classified into 6 class by neural network and is segmented into Jaso using the classification result the statistic vowel location information and the structural information. After Jaso segmentation, Hanguel recognition using neural network is performed. We experiment on four font of which three fonts are used for training the neural net and the rest is used of testing. Each font has the 2350 characters which are comprised in KS C 5601. The overall recognition rates for the training data and the testing data are 97,4% and 94&% respectively. This result shows the effectivness of proposed method.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.40 no.5
• /
• pp.266-279
• /
• 2003

In this paper, we propose machine printed character recognition methods which utilize the character type information and divide the character clusters. The characters are subdivided into a total of seven types, of which six types are for Hangul according to the grapheme combination fashions and one type for English characters, numerals, and symbols. According to the character type, we separate input character image into several recognition units and recognize them by using the direction angle feature. The recognition for each character type is completed by combining recognition units which are recognized by neural networks respectively For combining a total of seven character recognizers, we implemented seven methods such as switching method, integrating method, and their several variants. As experimental results, we obtained 98.2% recognition rate of simple switching method, 90.54% of integrating one, and between 97.35% and 98.65% of five variants.