scholarly journals Extended set of superpixel features

2021 ◽  
Vol 45 (4) ◽  
pp. 562-574
Author(s):  
A.A. Egorova ◽  
V.V. Sergeyev
Keyword(s):  
Image Processing ◽  
Computational Complexity ◽  
High Accuracy ◽  
Original Image ◽  
Superpixel Segmentation ◽  
Image Objects ◽  
Intensity Information ◽  
Small Set ◽  
Processing Algorithms

Superpixel-based image processing and analysis methods usually use a small set of superpixel features. Expanding the description of superpixels can improve the quality of processing algorithms. In the paper, a set of 25 basic superpixel features of shape, intensity, geometry, and location is proposed. The features meet the requirements of low computational complexity in the process of image superpixel segmentation and sufficiency for solving a wide class of application tasks. Applying the set, we present a modification of the well-known approach to the superpixel generation. It consists of fast primary superpixel segmentation of the image with a strict homogeneity predicate, which provides superpixels preserving the intensity information of the original image with high accuracy, and the subsequent enlargement of the superpixels with softer homogeneity predicates. The experiments show that the approach can significantly reduce the number of image elements, which helps to reduce the complexity of processing algorithms, meanwhile the expanded superpixels more accurately correspond to the image objects.

scholarly journals Image processing for cervical pathology diagnosis using cervix’s polarized images

2017 ◽  
Vol 20 (K3) ◽  
pp. 31-37
Author(s):  
Tien Van Tran ◽  
Cat Ngoc Phuong Phan ◽  
Linh Quang Huynh ◽  
Quynh Ngoc Nguyen ◽  
Hieu Trung Nguyen
Keyword(s):  
Quality Of Life ◽  
Image Processing ◽  
Early Detection ◽  
Trichomonas Vaginalis ◽  
Screening Methods ◽  
Treatment Plans ◽  
Suitable Treatment ◽  
Image Processing Algorithms ◽  
Processing Algorithms

Cervical pathologies are frequently occuring diseases and may affect women’s quality of life in many ways. These pathologies are curable with early detection and with a following suitable treatment plans. Colposcopy is a standard examination among screening methods which are used to early detect the abnormal lesions on cervix’s surface. Recently, studies about processing polarized image show ability to support diagnosis of the cervix. In this research, we use cervix’s polarized images and image processing algorithms to segment the blood distribution of Nabothian cyst and Trichomonas vaginalis infection. These results have the potential to provide underlying information of the cervix to support the diagnosis.

scholarly journals Enhancement of Satellite Imagesusing Image Sharpening Technique

2019 ◽  
Vol 8 (6S2) ◽  
pp. 351-354
Keyword(s):  
Image Processing ◽  
Color Image ◽  
Histogram Equalization ◽  
Grayscale Image ◽  
Original Image ◽  
High Quality ◽  
Wide Range ◽  
Equalization Technique ◽  
The Difference

In many image processing applications, a wide range of image enhancement techniques are being proposed. Many of these techniques demanda lot of critical and advance steps, but the resultingimage perception is not satisfactory. This paper proposes a novel sharpening method which is being experimented with additional steps. In the first step, the color image is transformed into grayscale image, then edge detection process is applied using Laplacian technique. Then deduct this image from the original image. The resulting image is as expected; After performing the enhancement process,the high quality of the image can be indicated using the Tenengrad criterion. The resulting image manifested the difference in certain areas, the dimension and the depth as well. Histogram equalization technique can also be applied to change the images color.

scholarly journals Using high-performance deep learning platform to accelerate object detection

2019 ◽  
pp. 354-360 ◽  
Author(s):  
S O Stepanenko ◽  
P Y Yakimov
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Image Processing ◽  
Processing Speed ◽  
High Performance ◽  
Object Classification ◽  
High Accuracy ◽  
Learning Platform ◽  
The Neural Network

Object classification with use of neural networks is extremely current today. YOLO is one of the most often used frameworks for object classification. It produces high accuracy but the processing speed is not high enough especially in conditions of limited performance of a computer. This article researches use of a framework called NVIDIA TensorRT to optimize YOLO with the aim of increasing the image processing speed. Saving efficiency and quality of the neural network work TensorRT allows us to increase the processing speed using an optimization of the architecture and an optimization of calculations on a GPU.

scholarly journals Stress Distribution Analysis on Hyperspectral Corn Leaf Images for Improved Phenotyping Quality

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3659
Author(s):  
Dongdong Ma ◽  
Liangju Wang ◽  
Libo Zhang ◽  
Zhihang Song ◽  
Tanzeel U. Rehman ◽  
...  
Keyword(s):  
Image Processing ◽  
Distribution Patterns ◽  
Plant Phenotyping ◽  
Distribution Analysis ◽  
Image Processing Algorithm ◽  
Plant Image ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Nitrogen Treatments

High-throughput imaging technologies have been developing rapidly for agricultural plant phenotyping purposes. With most of the current crop plant image processing algorithms, the plant canopy pixels are segmented from the images, and the averaged spectrum across the whole canopy is calculated in order to predict the plant’s physiological features. However, the nutrients and stress levels vary significantly across the canopy. For example, it is common to have several times of difference among Soil Plant Analysis Development (SPAD) chlorophyll meter readings of chlorophyll content at different positions on the same leaf. The current plant image processing algorithms cannot provide satisfactory plant measurement quality, as the averaged color cannot characterize the different leaf parts. Meanwhile, the nutrients and stress distribution patterns contain unique features which might provide valuable signals for phenotyping. There is great potential to develop a finer level of image processing algorithm which analyzes the nutrients and stress distributions across the leaf for improved quality of phenotyping measurements. In this paper, a new leaf image processing algorithm based on Random Forest and leaf region rescaling was developed in order to analyze the distribution patterns on the corn leaf. The normalized difference vegetation index (NDVI) was used as an example to demonstrate the improvements of the new algorithm in differentiating between different nitrogen stress levels. With the Random Forest method integrated into the algorithm, the distribution patterns along the corn leaf’s mid-rib direction were successfully modeled and utilized for improved phenotyping quality. The algorithm was tested in a field corn plant phenotyping assay with different genotypes and nitrogen treatments. Compared with the traditional image processing algorithms which average the NDVI (for example) throughout the whole leaf, the new algorithm more clearly differentiates the leaves from different nitrogen treatments and genotypes. We expect that, besides NDVI, the new distribution analysis algorithm could improve the quality of other plant feature measurements in similar ways.

A Seam Image Processing Method Based on Wavelet Compress

2012 ◽  
Vol 472-475 ◽  
pp. 1353-1356
Author(s):  
Guo Hong Ma ◽  
Cong Wang ◽  
Ze Hong Yang
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Image Compression ◽  
Compression Ratio ◽  
Processing Method ◽  
Original Image ◽  
Image Processing Method

This paper designs several common methods, which is applied to situation that seam image could keep the same format when it is compressed, then analyses several problems existing in image processing. According a comparison in sundry compress methods’ characteristics and application, this paper eventually chooses a compress method that is suitable to original image, which is based on wavelet transform image compression and coding. Compress experiments shows that, the image compression ratio this paper designs could be exceeded up to 0.74 on the condition of the same format. The quality of seam image is basically intact, which could provide a desirable method in seam image efficient transmit.

scholarly journals Pepper Powder Quality Identification System Based on Silent Angle Imagery

2020 ◽  
Vol 2 (1) ◽  
pp. 24
Author(s):  
Muhaimin Gusrin ◽  
Abdul Fadlil
Keyword(s):  
Image Processing ◽  
Research Method ◽  
Identification System ◽  
Original Image ◽  
Image Processing Techniques ◽  
Different Types ◽  
Angle Method ◽  
Pepper Powder ◽  
Processing Techniques

This research identifies the quality of pepper powder using a computer automatically. The research method uses the stationary angle method. The design of this system is done by image processing techniques. The image of ground pepper that has been taken is then cropped to remove the unused portion of the image. The next step is to convert the original image into grayscale and then convert it to binary. The parameter of the stationary angle is when it has an angle of less than or equal to 38 °, the ground pepper includes fine ground pepper. If the angle ranges from 38o to 40o, including medium powdered pepper, and if the angle is greater than 41o, including the texture of coarse pepper powder. Testing 3 different types of samples obtained 40 mesh is 35.18 o; for 20 mesh is 40.46o and 10 mesh is 41.66o. Therefore, it can be seen that the smaller the texture of the size of ground pepper, the finer the quality.Penelitian ini mengidentifikasi kualitas lada bubuk menggunakan komputer secara otomatis. Metode penelitian menggunakan metode sudut diam. Perancangan sistem ini dilakukan dengan teknik pengolahan citra. Citra lada bubuk yang telah diambil selanjutnya di-cropping untuk menghilangkan bagian citra yang tidak terpakai. Langkah selanjutnya adalah citra hasil asli tersebut dikonversi dalam bentuk grayscale dan selanjutnya dikonversi dalam bentuk biner. Parameter sudut diam adalah ketika memiliki sudut kurang dari atau sama dengan 38o, lada bubuk tersebut termasuk lada bubuk yang halus. Jika sudutnya berkisar antara 38o sampai 40o maka termasuk lada bubuk sedang, dan jika sudutnya lebih besar dari 41o maka termasuk tekstur lada bubuk kasar. Pengujian 3 jenis sampel yang berbeda didapatkan 40 mesh adalah 35,18o; untuk 20 mesh adalah 40,46o dan 10 mesh adalah 41,66o. Oleh karena itu dapat diketahui bahwa semakin kecil tekstur ukuran lada bubuk, semakin halus kualitasnya.

Otoconia perfect/imperfect crystals

1994 ◽  
Vol 52 ◽  
pp. 42-43
Author(s):  
César D. Fermin ◽  
Dale Martin
Keyword(s):  
Image Processing ◽  
Room Temperature ◽  
Phosphotungstic Acid ◽  
Gallus Domesticus ◽  
Crystal Matrix ◽  
Organic Templates ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Diffraction Patterns

Otoconia of higher vertebrates are interesting biological crystals that display the diffraction patterns of perfect crystals (e.g., calcite for birds and mammal) when intact, but fail to produce a regular crystallographic pattern when fixed. Image processing of the fixed crystal matrix, which resembles the organic templates of teeth and bone, failed to clarify a paradox of biomineralization described by Mann. Recently, we suggested that inner ear otoconia crystals contain growth plates that run in different directions, and that the arrangement of the plates may contribute to the turning angles seen at the hexagonal faces of the crystals.Using image processing algorithms described earlier, and Fourier Transform function (2FFT) of BioScan Optimas®, we evaluated the patterns in the packing of the otoconia fibrils of newly hatched chicks (Gallus domesticus) inner ears. Animals were fixed in situ by perfusion of 1% phosphotungstic acid (PTA) at room temperature through the left ventricle, after intraperitoneal Nembutal (35mg/Kg) deep anesthesia. Negatives were made with a Hitachi H-7100 TEM at 50K-400K magnifications. The negatives were then placed on a light box, where images were filtered and transferred to a 35 mm camera as described.

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