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Yazar "Dirik, Ahmet Emir" seçeneğine göre listele

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    Aktif Gürültü Kontrolü (ANC) Sisteminde Mikrofon ile Hoparlör Arasindaki Mesafenin Sistem Başarisina Etkisi
    (Institute of Electrical and Electronics Engineers Inc., 2024) Karşıyaka, Hikmet; Maden, Omer Faruk; Dirik, Ahmet Emir
    Active Noise Control (ANC) systems have increasingly become a prominent solution for reducing in-vehicle noise. This study investigates the impact of the distance between the microphone and the speaker on the performance of ANC systems. The positioning within the vehicle is a critical factor that directly affects both the accurate detection of noise frequencies by the microphone and the effective propagation of the anti-noise signal. Experimental studies and simulations were conducted on a system built using the 'Sigma Studio' software and Analog Devices 'ADAU1467'DSP chip to analyze the noise cancellation performance as a function of varying the distance between the microphone and the speaker. The results demonstrate that optimizing this distance yields more efficient noise cancellation, particularly for low frequency noises. These findings emphasize the significance of microphone and speaker placement in the design of in-vehicle ANC systems and provide strategies for improving future system efficiency. © 2024 IEEE.
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    Analysis of Rolling Shutter Effect on ENF-Based Video Forensics
    (Ieee-Inst Electrical Electronics Engineers Inc, 2019) Vatansever, Saffet; Dirik, Ahmet Emir; Memon, Nasir
    Electric network frequency (ENF) is a time-varying signal of the frequency of mains electricity in a power grid. It continuously fluctuates around a nominal value (50/60 Hz) clue to changes in the supply and demand of power over time. Depending on these ENF variations, the luminous intensity of a mains-powered light source also fluctuates. These fluctuations in luminance can he captured by video recordings. Accordingly, the ENF can he estimated from such videos by the analysis of steady content in the video scene. When videos are captured by using a rolling shutter sampling mechanism, as is done mostly with CMOS cameras, there is an idle period between successive frames. Consequently, a number of illumination samples of the scene are effectively lost due to the idle period. These missing samples affect the ENF estimation, in the sense of the frequency shift caused and the power attenuation that results. This paper develops an analytical model for videos captured using a rolling shutter mechanism. This model illustrates how the frequency of the main ENF harmonic varies depending on the idle period length, and how the power of the captured ENF attenuates as idle period increases. Based on this, a novel idle period estimation method for potential use in camera forensics that is able to operate independently of video frame rate is proposed. Finally, a novel time-of-recording verification approach based on the use of multiple ENF components, idle period assumptions, and the interpolation of missing ENF samples is also proposed.
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    Detecting the Presence of ENF Signal in Digital Videos: A Superpixel-Based Approach
    (Ieee-Inst Electrical Electronics Engineers Inc, 2017) Vatansever, Saffet; Dirik, Ahmet Emir; Memon, Nasir
    Electrical network frequency (ENF) instantaneously fluctuates around its nominal value (50/60 Hz) due to a continuous disparity between generated power and consumed power. Consequently, luminous intensity of a mains-powered light source varies depending on ENF fluctuations in the grid network. Variations in the luminance over time can be captured from video recordings and ENF can be estimated through content analysis of these recordings. In ENF-based video forensics, it is critical to check whether a given video file is appropriate for this type of analysis. That is, if ENF signal is not present in a given video, it would be useless to apply ENF-based forensic analysis. In this letter, an ENF signal presence detection method is introduced for videos. The proposed method is based on multiple ENF signal estimations from steady super pixels, i.e., pixels that are most likely uniform in color, brightness, and texture, and intra-class similarity of the estimated signals. Subsequently, consistency among these estimates is then used to determine the presence or absence of an ENF signal in a given video. The proposed technique can operate on video clips as short as 2 min and is independent of the camera sensor type, i.e., CCD or CMOS.
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    ENF Based Robust Media Time-Stamping
    (Ieee-Inst Electrical Electronics Engineers Inc, 2022) Vatansever, Saffet; Dirik, Ahmet Emir; Memon, Nasir
    Electric Network Frequency (ENF) continuously fluctuates around a nominal value (50/60 Hz) due to a persistent imbalance between supplied and demanded power. In certain circumstances, ENF gets intrinsically embedded into audio and video recordings and can be extracted from these recordings. Consequently, ENF can be used in a number of media forensic applications, such as verifying the time of recording of the media. In this work, a robust media time-stamping approach is proposed for media whose ENF content is relatively contaminated. It essentially entails two procedures: first, detecting all useful, i.e., considerably accurate, samples of an estimated ENF signal, and then applying an adapted normalized cross-correlation process that is designed for exploiting just the selected ENF portions based on a binary mask of the identified accurate samples. Experimental results show that the proposed approach provides significantly increased performance.
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    FACTORS AFFECTING ENF BASED TIME-OF-RECORDING ESTIMATION FOR VIDEO
    (Ieee, 2019) Vatansever, Saffet; Dirik, Ahmet Emir; Memon, Nasir
    ENF (Electric Network Frequency) oscillates around a nominal value (50/60 Hz) due to imbalance between consumed and generated power. The intensity of a light source powered by mains electricity varies depending on the ENF fluctuations. These fluctuations can be extracted from videos recorded in the presence of mains-powered source illumination. This work investigates how the quality of the ENF signal estimated from video is affected by different light source illumination, compression ratios, and by social media encoding. Also explored is the effect of the length of the ENF ground-truth database on time of recording detection and verification.
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    Factors Affecting Enf Based Time-of-recording Estimation for Video
    (Institute of Electrical and Electronics Engineers Inc., 2019) Vatansever, Saffet; Dirik, Ahmet Emir; Memon, Nasir D.
    ENF (Electric Network Frequency) oscillates around a nominal value (50/60 Hz) due to imbalance between consumed and generated power. The intensity of a light source powered by mains electricity varies depending on the ENF fluctuations. These fluctuations can be extracted from videos recorded in the presence of mains-powered source illumination. This work investigates how the quality of the ENF signal estimated from video is affected by different light source illumination, compression ratios, and by social media encoding. Also explored is the effect of the length of the ENF ground-truth database on time of recording detection and verification. © 2019 IEEE.
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    Farklı çözünürlükteki sayısal imge ve videolar için PRNU tabanlı kaynak kamera tespiti üzerine bir çalışma
    (2023) Vatansever, Saffet; Dirik, Ahmet Emir
    Her bir kamera sensörüne has benzersiz bir gürültü bileşeni olan PRNU (Photo Response Non-Uniformity), sayısal imge ve videoların adli analizi kapsamında ihtiyaç duyulan önemli araçlardandır. PRNU’nun en yaygın uygulama alanı olan kaynak kamera tespiti, aynı marka ve model kameraların bile PRNU karakteristiğinin birbirinden farklı oluşu ve bu örüntünün çekilen her bir resim karesi üzerine bir kamera parmak izi gibi istemsiz eklenmesi esasına dayanmaktadır. Bir test dosyasından (imge ya da video) kestirimi sağlanan PRNU sensör gürültüsü ile dosyanın kaynağı olduğu düşünülen kameraya ait referans PRNU (sabit içerikli düz duvar ya da gökyüzü görüntülerinden yüksek doğrulukta elde edilen PRNU örüntüsü) arasındaki benzerliğe göre bu kameranın test videosunun kaynağı olup olamayacağı belirlenebilir. Sayısal video çerçevelerinin imgelere göre düşük kalitede kodlanması, videolardan kestirilen PRNU sensör gürültüsünün doğruluğunu, dolayısıyla da benzerlik analizini etkilemektedir. Bu bağlamda, videolarda PRNU tabanlı kaynak kamera tespitinde, referans PRNU’nun videolardansa imgelerden elde edilmesi performans etkinliği için önemli bir hamledir. Ancak, imge ve videolar aynı kaynak kamera ile çekilmiş olsalar dahi farklı en boy oranında ve/veya çözünürlükte kaydedilmektedirler. Bu sebeple, imgelerden elde edilen PRNU izinin, sorgu videosuna ait PRNU sensör gürültüsü ile aynı foto-alıcı hücrelere karşılık gelecek forma dönüştürülmesi gerekmektedir. Bu çalışmada, bu dönüşümü sağlayan ölçekleme ve kırpma parametrelerini hassas bir şekilde hesaplayabilen bir yöntem önerilmiştir.
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    FAULT DIAGNOSIS WITH DEEP LEARNING FOR STANDARD AND ASYMMETRIC INVOLUTE SPUR GEARS
    (American Society of Mechanical Engineers (ASME), 2021) Karpat, Fatih; Dirik, Ahmet Emir; Kalay, Onur Can; Yüce, Celalettin; Doğan, Oğuz; Korcuklu, Burak
    Gears are critical power transmission elements used in various industries. However, varying working speeds and sudden load changes may cause root cracks, pitting, or missing tooth failures. The asymmetric tooth profile offers higher load-carrying capacity, long life, and the ability to lessen vibration than the standard (symmetric) profile spur gears. Gearbox faults that cannot be detected early may lead the entire system to stop or serious damage to the machine. In this regard, Deep Learning (DL) algorithms have started to be utilized for gear early fault diagnosis. This study aims to determine the root crack for both symmetric and asymmetric involute spur gears with a DL-based approach. To this end, single tooth stiffness of the gears was obtained with ANSYS software for healthy and cracked gears (50-100%), and then the time-varying mesh stiffness (TVMS) was calculated. A six-degrees-of-freedom dynamic model was developed by deriving the equations of motion of a single-stage spur gear mechanism. The vibration responses were collected for the healthy state, 50% and 100% crack degrees for both symmetric and asymmetric tooth profiles. Furthermore, the white Gaussian noise was added to the vibration data to complicate the early crack diagnosis task. The main contribution of this paper is that it adapts the DL-based approaches used for early fault diagnosis in standard profile involute spur gears to the asymmetric tooth concept for the first time. The proposed method can eliminate the need for large amounts of training data from costly physical experiments. Therefore, maintenance strategies can be improved by early crack detection.
  • Küçük Resim Yok
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    Forensic Analysis of Digital Audio Recordings based on Acoustic Mains Hum
    (Ieee, 2016) Vatansever, Saffet; Dirik, Ahmet Emir
    ENF (Electrical Network Frequency), fluctuates instantaneously from its nominal value (50/60 Hz) depending on an increase or decrease in power consumption as against power production in the grid network. An ENF-sourced noise component is added into audio recordings where mains power sourced electromagnetic field or acoustic mains hum exists. With the use of this component, recording date and time of an audio file can be verified. In this work, existence and estimation of the acoustic mains hum sourced ENF noise in audio files is studied by analysing the acoustic noise emitted by several devices that are frequently used at home or in workplace. Detection of the file recording time truly is examined by computation of the similarity between the ENF signals estimated from the audio recordings and the reference ENF obtained with the help of a circuit that is connected to power grid network. The behaviour of dynamic microphone and electret microphone towards acoustic mains hum is investigated and the extent of acquiring the information about recording device type and settings from audio files is analysed. Besides, as part of this work, ENF estimation from videos on social media is also investigated.
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    Measurement of Geometric Dimensions of Hexagonal Type Washer Parts Using Machine Vision-Based Systems
    (Institute of Electrical and Electronics Engineers Inc., 2024) Poyraz, Ahmet Gökhan; Dirik, Ahmet Emir; Gürkan, Hakan
    In this study, a method is proposed for measuring the geometric properties of hexagonal precision adjustment washers. The method primarily involves measuring the hypothetical diameter that encompasses the outermost part of the hexagon and the key slot dimensions of the hexagon. For the key slot dimension, subpixel-based edge detection is performed following a preprocessing step. Subsequently, the enclosing circle and diameter are estimated based on the detected points. For the key slot measurement, the first step involves Hough transform-based line detection. By predicting the equations of the detected lines, the distances between the opposing lines are computed. According to the results, both the proposed diameter measurement algorithm and the key slot measurement algorithm function with an average error of approximately 13 ?m in the utilized dataset. When considering part tolerances and average error amounts, it is concluded that the proposed algorithms are successful and feasible for practical use. © 2024 IEEE.
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    Sub-Pixel counting based diameter measurement algorithm for industrial Machine vision
    (Elsevier B.V., 2024) Poyraz, Ahmet Gökhan; Kaçmaz, Mehmet Ali; Gürkan, Hakan; Dirik, Ahmet Emir
    In recent years, there has been a notable surge in the utilization of industrial image processing applications across various sectors, including automotive, medical, and space industries. These applications rely on specialized camera systems and advanced image processing techniques to accurately measure working products with precise tolerances. This research presents a novel fast algorithm for measuring the diameter of a ring, employing a subpixel counting method. The algorithm classifies image pixels into two categories: full pixels and transition pixels. Full pixels reside entirely within the inner region of the workpiece, while transition pixels represent gray pixels that reside at the boundary between the workpiece and its background. To ensure accurate determination of the object area, the proposed method incorporates normalization to account for the contribution of transition pixels alongside full pixels. Subsequently, the circle area equation is employed to calculate the diameter. Moreover, a robust threshold selection method is introduced to effectively distinguish pixels with gray intensities. The experimental setup consists of an industrial camera equipped with telecentric lenses and appropriate illumination. The results demonstrate that the proposed algorithm achieves a 3–10 % improvement in accuracy compared to existing approaches. In terms of measuring sensitivity, the operational sensitivity of the proposed methodology is quantified as 1/20th of the pixel size, exhibiting an average uncertainty of 1 µm. Furthermore, the proposed method surpasses existing works by at least 12.5 % to 35 % in terms of benchmarking computing time. © 2023 Elsevier Ltd
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    The Effect of Inverse Square Law of Light on ENF in Videos Exposed by Rolling Shutter
    (Ieee-Inst Electrical Electronics Engineers Inc, 2023) Vatansever, Saffet; Dirik, Ahmet Emir; Memon, Nasir
    Due to a constant imbalance between demand and supply of power, ENF (Electric Network Frequency) fluctuates around a nominal value of 50 or 60 Hz. These variations in ENF cause the luminance intensity of a mains-powered light source, having no AC/DC converter inside, also to fluctuate. As a result, a video of a scene illuminated by a mains-powered light source can be used to estimate these fluctuations. As a consequence, the ENF signal within the time period when the video was captured can be estimated. This work explores the effects of frame rate harmonics that emerge when a rolling shutter based approach is used for ENF estimation from videos captured using CMOS cameras. These harmonics are a problem, especially for videos whose frame rate is a divisor of the nominal ENF because the frame rate harmonics and the ENF harmonics overlap. It is discovered that a key reason for the presence of the harmonics is the inverse square law of light that results in some repeating patterns of luminance variation across frames. This paper presents an analysis of the effect of the inverse square law of light on ENF estimation. A technique for refined ENF-related luminance signal estimation is proposed that attenuates these frame rate harmonics. This enables more accurate ENF estimates. The work also proposes an approach to estimate ENF-related luminance waveform cycles within each video frame, and a method to compute the confidence score for the estimated cycles. It provides insight into the reliability of the extracted ENF signal from a video, in the sense of its usefulness for ENF forensics, and consequently for ENF detection, which is an important precursor to ENF-based video forensics.
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    VİDEOLARIN ENF TABANLI ADLİ KANIT ANALİZİNE IŞIK KAYNAĞI ETKİSİ
    (2017) Vatansever, Saffet; Dirik, Ahmet Emir
    Video dosyalarının Elektrik Şebeke Frekansı (Electric Network Frequency - ENF) temelli adli kanıt analizi tekniği, çoklu ortam dosyalarının kayıt zamanını doğrulamada ve dosyalarda yapılan sahteciliği tespit etmede son yıllarda önerilmiş en önemli araçlardan biridir. ENF, şebekede üretilen toplam gücün tüketilen toplam güce göre artıp azalmasına bağlı olarak nominal değer (Avrupa"da 50 Hz) etrafında sürekli salınımlar yapar. Bu salınımlar aynı şebeke üzerindeki her noktada aynıdır. Elektrik şebekesinden beslenen bir ışık kaynağının yaymış olduğu aydınlatma şiddeti elektrik şebeke frekansına bağlı olarak insan gözünün fark edemeyeceği anlık değişkenlikler gösterir. Işık şiddetindeki bu değişimler, video kameralar tarafından yakalanabilmektedir. Çekilen videolardaki tüm resim çerçeveleri boyunca değişmeyen içerik analiz edilerek aydınlatma şiddetinin değişim hızı, dolayısıyla elektrik şebeke frekansı kestirilebilir. Videolardan kestirimi yapılan ENF sinyalinin, elektrik şebekesinden doğrudan elde edilen referans ENF sinyali ile benzerlikleri hesaplanarak dosya kayıt zamanı bilgisine ulaşılabilir. Bu çalışmada, şebeke elektriğine bağlı ışık kaynağı türünün, CCD sensörlü kamera ile çekilmiş videolardan kestirilen ENF sinyali kalitesinde ne derece etkili olduğu incelenmiştir. Işık kaynağı türüne göre, çeşitli uzunluktaki videolarda ENF temelli kayıt zamanı doğrulama performansı analiz edilmiştir.

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