Generation of filament winding patterns for elbows with various cross-sections

As a connecting component of tubes, the elbow is indispensable to pipe-fitting in composite products. Previous studies have addressed methods for generating winding paths based on parametric equations on the elbow. However, these methods are unsuitable for elbows whose surfaces are difficult to describe using mathematical expressions. In this study, a geometric method was proposed for generating winding patterns for various elbow types. With this method, the mandrel surface is first converted into uniform and high-quality quadrilateral elements; an algorithm is then provided for calculating the minimum winding angle for bridging-free. Next, an angle for non-bridging was defined as the design-winding angle to generate the uniform and slippage-free basic winding paths on the quadrilateral elements in non-geodesic directions. Finally, after a series of uniform points were calculated on the selected vertical edge according to the elbow type, the pattern paths were generated with the uniform points and basic paths. The proposed method is advantageously not limited to the elbow’s shape.

Vision-Based Lane Line Detection System

Since the 1990s, the rising key issue of the automobile industry is self-driving or driverless vehicles. Apparently, one of the most important challenges for smart self-driving cars comprises lane-detecting and lane-tracking capability to ensure safety and also decrease vehicle accidents for driver assistance systems. Since road lane detection is one of the most challenging tasks, driverless vehicles must learn to observe the road from a visual perspective in order to achieve automatic driving. Most of the research Works done so far can only detect the lanes or vehicles separately. However, in this paper, we propose a method to combine lane information and vehicle/obstacle information that can support the driver assistance system, driver warning system or the lane change assistant system so that it enhances the quality of results. For the lane changing system, the system detects or tracks the lane lines and detects the vehicles on all sides of a test vehicle. In lane detection, line detection algorithms such as the Canny Edge detection algorithm are used to detect the lane edges. Kalman filter will be used to track the vehicle detected from the vehicle detection algorithm. For vehicle detection, we use Otsu’s thresholding, horizontal edge filtering and vertical edge. The vertical edge filter and the Otsu’s thresholding are used to detect the vehicles on all sides of the test vehicles, then the horizontal edge is used to verify the vehicles detected.

Indonesian license plate recognition with improved horizontal-vertical edge projection

<p>License plate recognition (LPR) is one of the classical problems in the field of object recognition. Its application is very crucial in the automation of transportation system since it helps to recognise a vehicle identity, which information is stored in the license plate. LPR usually consists of three major phases: pre-processing, license plate localisation, optical character recognition (OCR). Despite being classical, its implementation faced with much more complicated problems in the real scenario. This paper proposed an improved LPR algorithm based on modified horizontal-vertical edge Projection. The method uses for detecting and localising the region of interest. It is done using the horizontal and vertical projection of the image. Related works proved that the modified horizontal-vertical edge projection is the simplest method to be implemented, yet very effective against Indonesian license plate. However, its performance gets reduced when specular reflection occurs in the sample image. Therefore, morphological operations are utilised in the pre-processing phase to reduce such effects while preserving the needed information. Eighty sample images which captured using various camera configurations were used in this research. Based on the experimental results, our proposed algorithm shows an improvement compared with the previous study and successfully detect 71 license plates in 80 image samples which results in 88.75% accuracy.</p>

IDENTIFIKASI PLAT MOBIL DENGAN MENGGUNAKAN METODE JARINGAN SYARAF TIRUAN KOHONEN PADA SISTEM PARKIR CERDAS

Masyarakat modern bepergian menggunakan kendaraan pribadi. Semakin banyaknya penggunaan kendaraan harus diimbangi dengan ketersediaan lahan parkir. Masalah ini dapat diatasi dengan membuat suatu system yang dapat mengetahui lokasi lahan parkir yang kosong untuk dapat di isi kendaraan. Identifikasi plat nomor menggunakan jaringan syaraf tiruan kohonen ini mempunyai beberapa tahapan, yaitu mobil yang memasuki lahan parkir akan melewati portal yang telah dipasangi webcam untuk mengambil citra dari mobil, lalu citra akan di resize dan melalui proses seperti grayscaling, vertical edge detection, dilasi, horizontal rank filter, lalu diperoleh lokasi plat nomor yang akan di identifikasi oleh program yang telah dibuat. Dilanjutkan dengan proses pemerataan latar belakang untuk memfokuskan program agar mendeteksi karakter dari plat nomor saja, tahap yang di lakukan pada proses ini antara lain adalah proses grayscaling, contrasting, binary, proses filter, dan membersihkan border dari plat. Selanjutnya proses mengekstraksi karakter satu per satu. Hasil di labelisasi itulah akan menjadi data inputan atau database untuk proses training, training menggunakan 3 sampel berbeda untuk setiap karakter nya. semakin banyak sampel semakin tinggi tingkat akurasi dari pembacaan program. Hasil dari uji coba program ini menghasilkan 65% keberhasilan mengenali pola huruf, 60% pola angka, dan 20% keberhasilan mengenali plat nomor dengan benar dari total percobaan 10 plat nomor.

Vehicle License Plate Recognition Based on Wavelet Transform and Vertical Edge Matching

With the improvement of our country’s economic level and quality of life, the numbers and scales of highway networks and motor vehicles are constantly expanding, which makes the current road traffic burden more and more serious. As an important means of traffic automation management, license plate recognition (LPR) technology plays an important role in traffic surveillance and control. However, the recognition rate and accuracy of the traditional license plate recognition methods still need to be improved. In the case of poor surrounding environment, it is prone to localization failure, vehicle license plate recognition errors or unrecognizable phenomena. Wavelet transform, as another landmark signal processing method after Fourier transform, has been widely used in the field of image processing. In China, the number of horizontal lines is usually larger than that of vertical lines. If the two vertical boundaries of the license plate can be detected successfully, the four angles of the license plate can be determined efficiently to complete the license plate positioning. In view of the advantages of wavelet transform technology and the characteristics of vehicle license plate, in this paper, a vehicle license plate recognition algorithm based on wavelet transform and vertical edge matching is proposed. The edge of the license plate is detected by wavelet transform technology, and then the license plate is located by vertical edge matching technology. After the location is realized, the characters are segmented by vertical projection method and the characters are recognized by improved BP neural network algorithm. The experimental results show that the proposed vehicle license plate recognition algorithm based on wavelet transform and vertical edge matching performs well in algorithm performance, which provides a good reference for the development of vehicle license plate recognition system.

Inkjet-printed co-continuous mesoporous oxides for high-current power transistors

Inkjet-printed co-continuous mesoporous structures have been demonstrated for a large set of functional oxides. Channel-length-independent electronic transport was achieved when the mesoporous oxides were used to obtain printed, vertical edge FETs.