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Features for Cross Spectral Image Matching: A Survey Maulisa Oktiana; Fitri Arnia; Yuwaldi Away; Khairul Munadi
Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

In recent years, cross spectral matching has been gaining attention in various biometric systems for identification and verification purposes. Cross spectral matching allows images taken under different electromagnetic spectrums to match each other. In cross spectral matching, one of the keys for successful matching is determined by the features used for representing an image. Therefore, the feature extraction step becomes an essential task. Researchers have improved matching accuracy by developing robust features. This paper presents most commonly selected features used in cross spectral matching. This survey covers basic concepts of cross spectral matching, visual and thermal features extraction, and state of the art descriptors. In the end, this paper provides a description of better feature selection methods in cross spectral matching.

Improving the Performance of CBIR on Islamic Women Apparels Using Normalized PHOG Cut Mutia; Fitri Arnia; Rusdha Muharar
Bulletin of Electrical Engineering and Informatics Vol 6, No 3: September 2017
Publisher : Institute of Advanced Engineering and Science

The designs of Islamic women apparels is dynamically changing, which can be shown by emerging of online shops selling clothing with fast updates of newest models. Traditionally, buying the clothes online can be done by querying the keywords to the retrieval system. The approach has a drawback that the keywords cannot describe the clothes designs precisely. Therefore, a searching based on content–known as content-based image retrieval (CBIR)–is required. One of the features used in CBIR is the shape. This article presents a new normalization approach to the Pyramid Histogram of Oriented Gradients (PHOG) as a mean for shape feature extraction of women Islamic clothing in a retrieval system. We refer to the proposed approach as normalized PHOG (NPHOG). The Euclidean distance measured the similarity of the clothing. The performance of the system was evaluated by using 340 clothing images, comprised of four clothing categories, 85 images for each category: blouse-pants, long dress, outerwear, and tunic. The recall and precision parameters measured the retrieval performance; the Histogram of Oriented Gradients (HOG) and PHOG were the methods for comparison. The experiments showed that NPHOG improved the HOG and PHOG performance in three clothing categories.

Improving the Performance of CBIR on Islamic Women Apparels Using Normalized PHOG Cut Mutia; Fitri Arnia; Rusdha Muharar
Bulletin of Electrical Engineering and Informatics Vol 6, No 3: September 2017
Publisher : Institute of Advanced Engineering and Science

The designs of Islamic women apparels is dynamically changing, which can be shown by emerging of online shops selling clothing with fast updates of newest models. Traditionally, buying the clothes online can be done by querying the keywords to the retrieval system. The approach has a drawback that the keywords cannot describe the clothes designs precisely. Therefore, a searching based on content–known as content-based image retrieval (CBIR)–is required. One of the features used in CBIR is the shape. This article presents a new normalization approach to the Pyramid Histogram of Oriented Gradients (PHOG) as a mean for shape feature extraction of women Islamic clothing in a retrieval system. We refer to the proposed approach as normalized PHOG (NPHOG). The Euclidean distance measured the similarity of the clothing. The performance of the system was evaluated by using 340 clothing images, comprised of four clothing categories, 85 images for each category: blouse-pants, long dress, outerwear, and tunic. The recall and precision parameters measured the retrieval performance; the Histogram of Oriented Gradients (HOG) and PHOG were the methods for comparison. The experiments showed that NPHOG improved the HOG and PHOG performance in three clothing categories.

Effectiveness of MPEG-7 Color Features in Clothing Retrieval Arsy Febrina Dewi; Fitri Arnia; Rusdha Muharar
Bulletin of Electrical Engineering and Informatics Vol 6, No 2: June 2017
Publisher : Institute of Advanced Engineering and Science

Clothing is a human used to cover the body. Clothing consist of dress, pants, skirts, and others. Clothing usually consists of various colors or a combination of several colors. Colors become one of the important reference used by humans in determining or looking for clothing according to their wishes. Color is one of the features that fit the human vision. Content Based Image Retrieval (CBIR) is a technique in Image Retrieval that give index to an image based on the characteristics contained in image such as color, shape, and texture. CBIR can make it easier to find something because it helps the grouping process on image based on its characteristic. In this case CBIR is used for the searching process of Muslim fashion based on the color features. The color used in this research is the color descriptor MPEG-7 which is Scalable Color Descriptor (SCD) and Dominant Color Descriptor (DCD). The SCD color feature displays the overall color proportion of the image, while the DCD displays the most dominant color in the image. For each image of Muslim women's clothing, the extraction process utilize SCD and DCD. This study used 150 images of Muslim women's clothing as a dataset consistingclass of red, blue, yellow, green and brown. Each class consists of 30 images. The similarity between the image features is measured using the eucludian distance. This study used human perception in viewing the color of clothing.The effectiveness is calculated for the color features of SCD and DCD adjusted to the human subjective similarity. Based on the simulation of effectiveness DCD result system gives higher value than SCD.

Features for Cross Spectral Image Matching: A Survey Maulisa Oktiana; Fitri Arnia; Yuwaldi Away; Khairul Munadi
Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v7i4.843

In recent years, cross spectral matching has been gaining attention in various biometric systems for identification and verification purposes. Cross spectral matching allows images taken under different electromagnetic spectrums to match each other. In cross spectral matching, one of the keys for successful matching is determined by the features used for representing an image. Therefore, the feature extraction step becomes an essential task. Researchers have improved matching accuracy by developing robust features. This paper presents most commonly selected features used in cross spectral matching. This survey covers basic concepts of cross spectral matching, visual and thermal features extraction, and state of the art descriptors. In the end, this paper provides a description of better feature selection methods in cross spectral matching.

Improving the Performance of CBIR on Islamic Women Apparels Using Normalized PHOG Cut Mutia; Fitri Arnia; Rusdha Muharar
Bulletin of Electrical Engineering and Informatics Vol 6, No 3: September 2017
Publisher : Institute of Advanced Engineering and Science

The designs of Islamic women apparels is dynamically changing, which can be shown by emerging of online shops selling clothing with fast updates of newest models. Traditionally, buying the clothes online can be done by querying the keywords to the retrieval system. The approach has a drawback that the keywords cannot describe the clothes designs precisely. Therefore, a searching based on content–known as content-based image retrieval (CBIR)–is required. One of the features used in CBIR is the shape. This article presents a new normalization approach to the Pyramid Histogram of Oriented Gradients (PHOG) as a mean for shape feature extraction of women Islamic clothing in a retrieval system. We refer to the proposed approach as normalized PHOG (NPHOG). The Euclidean distance measured the similarity of the clothing. The performance of the system was evaluated by using 340 clothing images, comprised of four clothing categories, 85 images for each category: blouse-pants, long dress, outerwear, and tunic. The recall and precision parameters measured the retrieval performance; the Histogram of Oriented Gradients (HOG) and PHOG were the methods for comparison. The experiments showed that NPHOG improved the HOG and PHOG performance in three clothing categories.

Effectiveness of MPEG-7 Color Features in Clothing Retrieval Arsy Febrina Dewi; Fitri Arnia; Rusdha Muharar
Bulletin of Electrical Engineering and Informatics Vol 6, No 2: June 2017
Publisher : Institute of Advanced Engineering and Science

Clothing is a human used to cover the body. Clothing consist of dress, pants, skirts, and others. Clothing usually consists of various colors or a combination of several colors. Colors become one of the important reference used by humans in determining or looking for clothing according to their wishes. Color is one of the features that fit the human vision. Content Based Image Retrieval (CBIR) is a technique in Image Retrieval that give index to an image based on the characteristics contained in image such as color, shape, and texture. CBIR can make it easier to find something because it helps the grouping process on image based on its characteristic. In this case CBIR is used for the searching process of Muslim fashion based on the color features. The color used in this research is the color descriptor MPEG-7 which is Scalable Color Descriptor (SCD) and Dominant Color Descriptor (DCD). The SCD color feature displays the overall color proportion of the image, while the DCD displays the most dominant color in the image. For each image of Muslim women's clothing, the extraction process utilize SCD and DCD. This study used 150 images of Muslim women's clothing as a dataset consistingclass of red, blue, yellow, green and brown. Each class consists of 30 images. The similarity between the image features is measured using the eucludian distance. This study used human perception in viewing the color of clothing.The effectiveness is calculated for the color features of SCD and DCD adjusted to the human subjective similarity. Based on the simulation of effectiveness DCD result system gives higher value than SCD.

Features for Cross Spectral Image Matching: A Survey Maulisa Oktiana; Fitri Arnia; Yuwaldi Away; Khairul Munadi
Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

In recent years, cross spectral matching has been gaining attention in various biometric systems for identification and verification purposes. Cross spectral matching allows images taken under different electromagnetic spectrums to match each other. In cross spectral matching, one of the keys for successful matching is determined by the features used for representing an image. Therefore, the feature extraction step becomes an essential task. Researchers have improved matching accuracy by developing robust features. This paper presents most commonly selected features used in cross spectral matching. This survey covers basic concepts of cross spectral matching, visual and thermal features extraction, and state of the art descriptors. In the end, this paper provides a description of better feature selection methods in cross spectral matching.

Metode Band-Limited Phase Only Correlation (BLPOC) untuk Identifikasi Plat Kendaraan Fitri Arnia; Syahrul Wahyudi; Siti Aisyah
Jurnal Rekayasa Elektrika Vol 10, No 1 (2012)
Publisher : Universitas Syiah Kuala

Digital image processing and computer vision technologies have developed so rapidly and have numerous applications. Automatic lisence plate recognition systems (ALPRS) based on those technologies are not exceptions. In general, the ALPRSs required several steps including image capturing, plate location searching, character segmentation and character recognition. Successful of the whole systems depended heavily on the used segmentation method. A common drawback of many segmentation techniques is that they are very sensitive to illumination variability. The paper proposed a method for license plate recognition based on correlation of phase componenet with limited bandwidth. The method is widely known as band-limited phase only correlation (BLPOC). The method compared input plate’s image with plate’s images in the database. Based on simulation, detection rate can achieve 90% if an appropriate threshold value was selected.

Simulasi Pelacakan Titik Daya Maksimum Modul Surya dengan Metode Grey Wolf Optimization Rizki Faulianur; Ira Devi Sara; Fitri Arnia
Jurnal Rekayasa Elektrika Vol 14, No 1 (2018)
Publisher : Universitas Syiah Kuala

The photovoltaic module has a nonlinear current and voltage characteristic curve where there is a maximum power point to be tracked to avoid wasted energy. Some methods for tracking the maximum power points have been developed such as perturb and observe (P O), Incremental Conductance (IC), and Hill Climbing (HC). However, those methods were not so accurate to find the maximum power point and they were also slow to respond the changes in solar radiation and temperature. To overcome the shortcomings of the method, a new optimization approach was developed. This method is called Gray Wolf Optimization (GWO). It work based on the wolf behavior in capturing the prey. In this study, it will be determined to what extent the GWO method can track the maximum working point of solar modules that undergo changes in radiation and working temperature quickly and accurately. This research was conducted by simulation using Matlab/Simulink by comparing the extract of power GWO method with its power characteristics. The results obtained by the GWO method trace maximum power with an average accuracy rate of 99.14 % with time less than 0.1 second. From this data, it can be concluded that the GWO method successfully responds well and accurately to changes in radiation and temperature.

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