Introduction: Extensive development of written interactions in the current world of technology in one hand, and noticeable dominance of English language in this milieu on the other hand, has led to inadequate utilization of Farsi language even amongst native speakers. Lack of experimental data regarding legibility and readability of printed and electronic texts related to this language has been the main theory behind the current research, which was designed to evaluate correlations between typography and reading performance.Materials and Methods: Eighty-four Persian speaking university students, without any specific visual impairments participated in the study. Frequently used Farsi FONTs, edited in equal pixel areas and sizes, were evaluated through legibility and readability tests. Word detection and word search techniques were considered for each test. All trails were designed within similar visual interaction conditions to avoid any background biases.Results: Statistical analyses revealed correlations between typography and readying performance in Farsi (compared to English). Amongst six frequently used FONTs studied, legibility was significantly higher in Yekan (t(83)=-2.649, p=0.012). Likewise, readability was significantly smoother in Zar FONT (t(83)=-2.194, p=0.037).Conclusion: The current approach towards classification of Persian FONTs confirms the outcomes of the present study. FONTs frequently used for development of body of the texts usually have higher legibility, and types used for presentation purposes mainly possess higher readability.

Background and Objective: Medication errors are recognized as a serious threat to patient safety that can lead to adverse health outcomes and increased healthcare costs. This study evaluated the impact of FONT size, FONT type, and correlated color temperature (CCT) on the readability of printed medication prescriptions. Materials and Methods: This experimental study was conducted at an education hospital with the participation of 30 nurses. Four levels of correlated color temperature (CCT) (2885, 4003, 6132, and 9973 K) at a constant illuminance of 150 lx, along with three FONT types (Tahoma, Zar, and Yekan) in three different sizes (9, 11, and 13 pt) were evaluated. Data analysis was performed using linear mixed models (LMM). Results: The results revealed that CCT has a significant effect on readability. The highest error rate was observed at 2885 K, significantly greater than 6132 K (P = 0.004) and 9973 K (P = 0.002). FONT size also had a significant impact, with FONT size 9 pt producing more errors than sizes 11 and 13. No significant effect was observed for FONT type. Subjectively, except for irritability, other variables, including adequacy of amount and color of illumination, light distribution, pleasantness, performance, and sleepiness, did not exhibit significant differences among the various lighting conditions. Conclusion: The findings highlight the importance of optimizing lighting conditions and typographic characteristics in reducing readability errors in medication prescriptions. However, further studies are necessary to determine the optimal lighting parameters and their interaction with typographic variables.

This paper presents a new method based on a combination of features and classifiers for FONT. Features are extracted and combined from textures of 128×128 pixels size. For feature extraction, Sobel-Roberts Features, Gabor Filter and different Wavelet transform same as Daubechies and Haar are employed. Extracted features combined together in a pairwise manner. Three MLP (Multi Layer Perceptron) used for classification, the MLPs run on different features. Then their output combined together by employing PSO (Position swarm optimization) algorithm for finding optimum weights. Experimental results have also verified this hypothesis. The proposed algorithm is examined on the Hoda dataset of 21000 samples prepared from 10 different Farsi FONTs. The characteristics of the FONTs are properly extracted in the method adopted by this research, achieved 97.45% accuracy in recognition rates so it has outperformed previous contributions and higher recognition rates.

Farsi FONT detection is considered as the first stage in the Farsi optical character recognition (FOCR) of scanned printed texts. To this aim, this paper proposes an improved version of the speeded-up robust features (SURF) algorithm, as the feature detector in the FONT recognition process. The SURF algorithm suffers from creation of several redundant features during the detection phase. Thus, the presented version employs the redundant keypoint elimination method (RKEM) to enhance the matching performance of the SURF by reducing unnecessary keypoints. Although the performance of the RKEM is acceptable in this task, it exploits a fixed experimental threshold value which has a detrimental impact on the results. In this paper, an Adaptive RKEM is proposed for the SURF algorithm which considers image type and distortion, when adjusting the threshold value. Then, this improved version is applied to recognize Farsi FONTs in texts. To do this, the proposed Adaptive RKEM-SURF detects the keypoints and then SURF is used as the descriptor for the features. Finally, the matching process is done using the nearest neighbor distance ratio. The proposed approach is compared with recently published algorithms for FOCR to confirm its superiority. This method has the capability to be generalized to other languages such as Arabic and English.

In this paper, a clustering algorithm for printed Farsi subwords is presented, which is based on a pictorial dictionary. To build this dicitonary, the upper contour of each subword is segmented into the labeled strokes. According to these labels, an index is given to each subword. The subwords having the same index, make their own group or neighborhood in the dictionary. The neighboring subwords are further clustered based on their salient characters. The pictorial dictionary was built using the bodies of 2772 subwords with 2, 3 and 4 characters. For each subword, 25 samples in 5 different FONTs are included. The average neighborhood size and the average cluster size were 74.37 and 4.3 subwords respectively. In an experiment on the same database, the samples of one FONT were left out for the test, and the dictionary was built using the remaining samples. 98.61% of the test samples were assigned to the correct cluster.

In past the needs of society, including business competition in the form of advertisements, posters, newspapers, books and other publications, provide an opportunity for designer till they operate new art forms for creating new visual expression. Nowadays, with entering computer into human life and transferring information with it, the media isn’ t limited to print media. Increasing life speed and volume data, which human concern it, is led to appear virtual media. They operate much stronger and faster than other media. Virtual space is an environment that is constructed by invisible information which can take different forms to itself. In fact, cyberspace can be used to describe all kinds of infomative resources in networks. Therefore, virtual space is a different type of a virtual, digital reality that is constructed in computer networks and can be considered a synonym with the World Wide Web. FONT design, in its historical line direction, has been dependent on technological capabilities and long with, it started to optimize traditional calligraphy in new technology space. At present, with the growing volume of data and the need for rapid transmission, print media deposits a significant contribution to digital media in cyber space and this share is increasing every moment. Now we need a specifically FONT design in media. At the beginning of the boom of digital media, web designers used standards FONT for displaying their own texts and the public of Persian language websites used “ Tahoma” as a standards FONT. With advent of web FONTs possibility to use FONTs that was not existent in users’ system. Therefore, when the designers are using of web FONTs, they ensure that the last users’ screen visit this page with their desired FONT. However, despite remedying problem in displaying FONTs in cyberspace as well as Tahoma is the most widely used among Persian language speaker. Nowadays, it is believed that Tahoma is the most appropriate FONTs for Persian writing in webpages. Perhaps the reason is that the users’ eyes get used to the see these FONTs like Tahoma, which existed from the beginning and they are inattentive to its strengths and weakness. It seems that this FONT is far from Persian calligraphy principles and it is used for its abundant coordination with web space structure. On this line, this paper is proceeded to basic aim in studding of the conformity "Tahoma" FONT with formic structure in Persian letters and examining the similarities and differences that are based on the comparative studding on this FONT structure and four important principles in the Persian Naskh calligraphy which include: principle, proportionality, composition and the baseline. The result shows that many changes which is used in Tahoma is only based on designer's lake of adequate knowledge from Persian calligraphy and there is no relevance in maintaining readability of the letters in pixel space. Also one of the reasons that user's wide pearly use from this FONT can be supported by most browsers and there is a coordination rate between this FONTs with screen.