Given an image with N blocks of 8x8 pixels, we construct an indexing key by overlapping the N blocks into one combinational block and each block acting as one single plane inside the combinational block. Specific construction of each element inside the indexing key can have a range of alternatives based on such a common platform. These include: (i) average DCT value (ii) energy distributed in DCT domain to construct the indexing key, and (iii) DCT coefficients that can be polarized via exploiting their directional properties, and thus can be processed to construct an energy magnitude to highlight the texture of the input image. In this way, the dimension of the indexing key can be significantly reduced. In this paper we represent DCT descriptors as tools of generating indexing key in compress domain. General TermsImage Retrieval
The application of electronic learning is carried out in the learning process at Patria Gadingrejo Vocational School to determine the factors that are still weak or require improvement and the factors that are considered successful or strong in assisting the application of electronic learning in the learning process. This study results in Aydin and Tasci's ELR model questionnaire consisting of 37 statements grouped into four factors. These factors are human, self-development, technology, and innovation as well as six questions for the perception of the usefulness of electronic learning. The location of this research is at Patria Gadingrejo Vocational School. Respondents in this study were the principal, vice principal of the curriculum section, the school treasurer, the person in charge of the school computer laboratory, and teachers who are experts in e-learning. Data processing is carried out to examine the factors that influence the perceived usefulness of e-learning by using regression analysis and also the level of readiness for the application of electronic learning at Patria Gadingrejo Vocational School with Aydin and Tasci's ELR model. Aydin & Tasci's electronic learning readiness (ELR) model applied to Patria Gadingrejo Vocational School gives results that are not ready for the application of electronic learning and requires a slight improvement.
Purpose: Face recognition is a geometric space recording activity that allows it to be used to distinguish the features of a face. Therefore, facial recognition can be used to identify ID cards, ATM card PINs, search for one’s committed crimes, terrorists, and other criminals whose faces were not caught by Close-Circuit Television (CCTV). Based on the face image database and by applying the Content-Base Image Retrieval method (CBIR), committed crimes can be recognized on his face. Moreover, the image segmentation technique was carried out before CBIR was applied. This work tried to recognize an individual who committed crimes based on his or her face by using sketch facial images as a query. Methods: We used an image sketch as a querybecause CCTV could not have caught the face image. The research used no less than 1,000 facial images were carried out, both normal as well asabnormal faces (with obstacles). Findings:Experiments demonstrated good enough in terms of precision and recall, which are 0,8 and 0,3 respectively, which is better than at least two previous works.The work demonstrates a precision of 80% which means retrieval of effectiveness is good enough. The 75 queries were carried out in this work to compute the precision and recall of image retrieval. Novelty: Most face recognition researchers using CBIR employed an image as a query. Furthermore, previous work still rarely applied image segmentation as well as CBIR.
Role of the student attendance record is very important in the primary, secondary, and tertiary education. The purpose of this record is monitoring student activity in the teaching and learning process and regarded as one of the important learning assessments. Moreover, a data processing for recording the student attendance is currently done in various ways such as fingerprint, radio frequent identification (RFID), facial recognition system, android-based application, and others. However, many conventional ways (i.e., using paper-based system) are still used, especially in Indonesia. This is because several universities still rarely have enough funds for developing innovative systems. In this research, the image processing application for capturing student attendance data was built. The objective of this research was to provide an efficient alternative to monitor student activities in teaching and learning process. The image processing produced the information related to student attendance by scanning the attendance file through jpg/jpeg using learning vector quantization (LVG) as the process model.
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