An adaptive edge-enhanced correlation based robust and real-time visual tracking framework, and two machine vision systems based on the framework are proposed. The visual tracking algorithm can track any object of interest in a video acquired from a stationary or moving camera. It can handle the real-world problems, such as noise, clutter, occlusion, uneven illumination, varying appearance, orientation, scale, and velocity of the maneuvering object, and object fading and obscuration in low contrast video at various zoom levels. The proposed machine vision systems are an active camera tracking system and a vision based system for a UGV (unmanned ground vehicle) to handle a road intersection. The core of the proposed visual tracking framework is an Edge Enhanced Back-propagation neural-network Controlled Fast Normalized Correlation (EE- BCFNC), which makes the object localization stage efficient and robust to noise, object fading, obscuration, and uneven illumination. The incorrect template initialization and template-drift problems of the traditional correlation tracker are handled by a best-match rectangle adjustment algorithm. The varying appearance of the object and the short-term neighboring clutter are addressed by a robust template- updating scheme. The background clutter and varying velocity of the object are handled by looking for the object only in a dynamically resizable search window, in which the likelihood of the presence of the object is high. The search window is created using the prediction and the prediction error of a Kalman filter. The effect of the long-term neighboring clutter is reduced by weighting the template pixels using a 2D Gaussian weighting window with adaptive standard deviation parameters. The occlusion is addressed by a data association technique. The varying scale of the object is handled by correlating the search window with three scales of the template, and accepting the best-match region that produces the highest peak in the three correlation surfaces. The proposed visual tracking algorithm is compared with the traditional correlation tracker and, in some cases, with the mean-shift and the condensation trackers on real-world imagery. The proposed algorithm outperforms them in robustness and executes at the speed of 25 to 75 frames/second depending on the current sizes of the adaptive template and the dynamic search window. The proposed active camera tracking system can be used to get the target always in focus (i.e. in the center of the video frame) regardless of the motion of the target in the scene. It feeds the target coordinates estimated by the visual tracking framework into a predictive open-loop car-following control (POL-CFC) algorithm which in turn generates the precise control signals for the pan-tilt motion of the camera. The performance analysis of the system shows that its percent overshoot, rise time, and maximum steady state error are 0%, 1.7 second, and ±1 pixel, respectively. The hardware of the proposed vision based system, that enables a UGV to handle a road intersection, consists of three on-board computers and three cameras (mounted on top of the UGV) looking towards the other three roads merging at the intersection. The software in each computer consists of a vehicle detector, the proposed tracker, and a finite state machine model (FSM) of the traffic. The information from the three FSMs is combined to make an autonomous decision whether it is safe for the UGV to cross the intersection or not. The results of the actual UGV experiments are provided to validate the robustness of the proposed system. Index terms – visual tracking, adaptive edge-enhanced correlation, active camera, unmanned ground vehicle.
The Immensely Merciful to all, The Infinitely Compassionate to everyone.
30:01 a. Alif. Lam. Mim.
30:02 a. The Byzantines have been defeated,
30:03 a. in the nearby land, b. yet after their defeat, they will be victorious once again over their Persian enemy…..
30:04 a. within a few years - b. for their affair belongs to Allah - The One and Only God - from beginning to end, c. and at that time of victory, the believers will celebrate -
30:05 a. It all happens with Allah’s help. b. HE Helps whoever HE Wills to victory, c. for HE is The Almighty, The Ever-Compassionate.
30:06 a. This is the firm Promise of Allah, b. and Allah never breaks HIS Promise, c. even though most people do not understand it.
30:07 a. They only understand what is apparent in this worldly life, b. but they are oblivious of the realm of the Hereafter.
30:08 a. Would they never contemplate within themselves so as to emerge from their oblivion? b. Allah did not create the celestial realm and the terrestrial world, and whatever is between and beyond them, except in truth, and for a specified term. c. Even so, many people are disbelievers in the Meeting with their Rabb - The Lord.
30:09 a. Have they never traveled around the world and visited the archaeological sites and seen the fate of those civilizations who were before them? b. In fact, they were even more powerful than them - such as ‘Ad, Thamud, and Tubba’, and
Keberadaan seorang customer service sangat diperlukan didalam organisasi perusahaan, agar dapat berfungsi sebagai fungsi manajemen modern yang mempunyai fungsi melekat pada manajemen perusahaan, yakni bagaimana berperan dalam melakukan komunikasi timbal balik untuk tujuan menciptakan saling pengertian, saling menghargai, saling mempercayai menciptakan goodwill, memperoleh dukungan masyarakat dan sebagainya demi tercapainya citra yang positif bagi suatu perusahaan. Perkembangan masyarakat dewasa ini menghendaki agar tiap-tiap perusahaan perlu mengatur hubungannya melalui pelayanan dengan berbagai keputusan masyarakat agar tercapai hubungan yang serasi dan harmonis. Penelitian ini bertujuan untuk mengetahui dan menganalisis peranan customer service Terhadap Pelayanan Jasa Kredit Pada PT. Pegadaian Cabang Gunungsitoli. Sampel penelitian ini diambil dengan menggunakan metode random sampling (sampling acak). Penelitian ini menggunakan pendekatan kualitatif yang datanya diolah melalui tiga jalur analisis data kualitatif yaitu reduksi data, penyajian data dan penarikan kesimpulan.
The performance of Content Based Image Retrieval (CBIR) is limited because of the Semantic Gap (SG). This motivates to extend the image retrieval process beyond low level descriptions to image semantics. Therefore, researchers proposed Semantic Based Image Retrieval (SBIR) to bridge SG. In the literature, various approaches for SBIR such as image annotation, relevance feedback, and object ontology have been proposed to bridge SG. It has been observed that not very promising results with these methods are reported in the literature. Annotation based approaches are constrained by low precision because real life images usually have a diverse set of image concepts. Relevance feedback approach is also constrained by low precision and recall because it forces to alter the query vector that causes to modify image semantics. Object ontology is a considerably good approach, but its metadata architecture appears to be very complex and suggested to use only for semantic web instead of SBIR. Moreover, this approach is reported to have low precision for conceptually diverse images. Therefore, the first contribution of our work is the performance evaluation of CBIR methods using soft computing techniques for image comparison and retrieval. In this regard, we have reported performance improvement in terms of retrieving visually similar images by employing proposed modifications in soft computing methods. However, these modifications do not translate into semantically correct retrieval of images. This leads us towards the logical conclusion of planning and development of a new SBIR framework using image concepts. By the term “image concept” we means that a set of noticeable objects and regions in an image e.g. Sky, group of person, land etc. In our first contribution we have also explored existing CBIR approaches in order to find a suitable 11 candidate (or its modified version) to be used for SBIR. The second contribution of our work is therefore to bridge the SG with a maximum tradeoff between precision and recall. The proposed framework is extensively examined by evaluating precision and recall for large segmented datasets. For the rigorous testing of our major contributions, three datasets have been opted, namely, Wang’s, COIL, and IAPR TC-12.