Mature pomegranate recognition methods in natural environments using machine vision / Métodos de reconhecimento de romã madura em ambientes naturais usando visão de máquina

ABSTRACT: The use of machine vision to recognize mature pomegranates in natural environments is of major significance in improving the applicability and work efficiency of picking robots. By analyzing the color characteristics of color images of mature pomegranates under different illumination conditions, the feasibility of the YCbCr color model for pomegranate image recognition under different illumination conditions was proven. First, the Cr component map of pomegranate image is selected and then the pomegranate fruit is segmented by the kernel fuzzy C-means clustering algorithm to obtain the pomegranate image. Contrast experiments of pomegranate image segmentation under different illumination conditions were then performed using the proposed kernel fuzzy C-means clustering algorithm, the fuzzy C-means clustering algorithm, the Otsu algorithm and the threshold segmentation algorithm. Results of the experiments verified the effectiveness and superiority of the proposed algorithm.

RESUMO: O uso de máquina para reconhecer romãs maduras em ambientes naturais é de grande importância para melhorar a aplicabilidade e a eficiência do trabalho de robôs de colheita. Ao analisar as características de cor das imagens coloridas de romãs maduras sob diferentes condições de iluminação, a viabilidade do modelo de cores YCbCr para o reconhecimento de imagens de romãs sob diferentes condições de iluminação foi comprovada. Primeiro, o mapa do componente Cr da imagem da romã é selecionado e, em seguida, o fruto da romãzeira é segmentado pelo algoritmo de agrupamento C-means fuzzy do kernel para obter a imagem da romã. Experimentos contrastados de segmentação de imagens de romã sob diferentes condições de iluminação foram então realizados usando o algoritmo proposto de agrupamento C-means fuzzy, o algoritmo fuzzy de agrupamento C-means, o algoritmo Otsu e o algoritmo de segmentação de limiares. Os resultados dos experimentos verificaram a efetividade e superioridade do algoritmo proposto.

Preliminary clinical application of fluorescence microscopic imaging and computer-aided diagnosis system in the diagnosis of superficial cutaneous fungal infections / 中华皮肤科杂志

Objective To evaluate the accuracy of automated fluorescence microscopic imaging and computer-aided diagnosis system (AFMICADS) in the auxiliary diagnosis of superficial cutaneous fungal infections.Methods Totally,106 outpatients and inpatients with suspected superficial fungal infections were enrolled from clinical departments of Union Hospital,Tongji Medical College,Huazhong University of Science and Technology between July 2018 and September 2018.A total of 126 specimens were collected,including 83 skin scales and 43 nail parings.Each specimen was divided into 3 groups to be examined by conventional fungal microscopy,culture with modified Sabouraud dextrose agar and fluorescence microscopy (artificial fluorescence microscopy and AFMICADS-based fluorescence microscopy) respectively.A positive result was defined as that conventional fungal microscopy and/or fungal culture was positive.Consistency rate,sensitivity and specificity of the 3 microscopic methods were calculated.Statistical analysis was carried out with SPSS 10.0 software by using McNemar test and Kappa test for analyzing difference in the positive rate,as well as consistency,between the 3 microscopic methods and the positive standard,and by using efficiency test for comparing the consistency rate among the 3 microscopic methods.Results Of 126 specimens,124 (98.4％) were positive for artificial fluorescence microscopy,and 123 (97.6％) for AFMICADS-based fluorescence microscopy.Both positive rates of the above 2 microscopic methods were significantly higher than the positive rate of the positive standard (77.8％,both P ＜ 0.001).The sensitivity,specificity and consistency rate of AFMICADS-based fluorescence microscopy were 100％,10.7％ and 80.2％ respectively,and those of artificial fluorescence microscopy were 100％,7.1％ and 79.4％ respectively.Additionally,no significant difference in the consistency was observed between the AFMICADS-based and artificial fluorescence microscopy (P ＞0.05).Conclusion The accuracy of AFMICADS-based fluorescence microscopy in the diagnosis of superficial cutaneous fungal infections is similar to that of artificial fluorescence microscopy.

Preliminary clinical application of fluorescence microscopic imaging and computer-aided diagnosis system in the diagnosis of superficial cutaneous fungal infections / 中华皮肤科杂志

Objective@#To evaluate the accuracy of automated fluorescence microscopic imaging and computer-aided diagnosis system (AFMICADS) in the auxiliary diagnosis of superficial cutaneous fungal infections.@*Methods@#Totally, 106 outpatients and inpatients with suspected superficial fungal infections were enrolled from clinical departments of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology between July 2018 and September 2018. A total of 126 specimens were collected, including 83 skin scales and 43 nail parings. Each specimen was divided into 3 groups to be examined by conventional fungal microscopy, culture with modified Sabouraud dextrose agar and fluorescence microscopy (artificial fluorescence microscopy and AFMICADS-based fluorescence microscopy) respectively. A positive result was defined as that conventional fungal microscopy and/or fungal culture was positive. Consistency rate, sensitivity and specificity of the 3 microscopic methods were calculated. Statistical analysis was carried out with SPSS 10.0 software by using McNemar test and Kappa test for analyzing difference in the positive rate, as well as consistency, between the 3 microscopic methods and the positive standard, and by using efficiency test for comparing the consistency rate among the 3 microscopic methods.@*Results@#Of 126 specimens, 124 (98.4%) were positive for artificial fluorescence microscopy, and 123 (97.6%) for AFMICADS-based fluorescence microscopy. Both positive rates of the above 2 microscopic methods were significantly higher than the positive rate of the positive standard (77.8%, both P < 0.001) . The sensitivity, specificity and consistency rate of AFMICADS-based fluorescence microscopy were 100%, 10.7% and 80.2% respectively, and those of artificial fluorescence microscopy were 100%, 7.1% and 79.4% respectively. Additionally, no significant difference in the consistency was observed between the AFMICADS-based and artificial fluorescence microscopy (P > 0.05) .@*Conclusion@#The accuracy of AFMICADS-based fluorescence microscopy in the diagnosis of superficial cutaneous fungal infections is similar to that of artificial fluorescence microscopy.

Road Condition Identification of Intelligent Lower Limb Prosthesis Based on Visual Information / 中国康复理论与实践

@#Objective To carry out a research of terrain recognition on intelligent knee joint from the perspective of pure visual information.Methods The whole experimental environment was illuminated by halogen lamp, which made the brightness and color temperature of the set scene change less. The machine vision module was embedded in the intelligent knee joint control system. The road image data was collected by the camera in real time, and the captured image was processed in grayscale. The normalized cross correlation algorithm (NCC) was used to match the image pattern to identify the corresponding road conditions.Results The accuracy rates of the road vision, up/down hill, and up/down stairs recognized by the machine vision module were 88.6%, 85.3%, 78.4%, 87.5%, and 77.9%, respectively. The recognition effect was good, and the recognition time was within one second, real-time performance was strong.Conclusion The effectiveness and feasibility of intelligent knee joint prosthetic road condition recognition based on pure visual information is proved.

Quality evaluation method for Chinese medicine based on color grading / 中国中药杂志

Traditional identification method is an effective approach to evaluate the quality for Chinese herbal medicine (CHM). Color is one of the important indicators for quality evaluation due to high correlation with quality. Therefore, a new theory of quality control for CHM based on color grading was discussed in this article. The scientific nature of this theory was illustrated by investigating the relation between CHM color, medicinal properties and active compound contents. The effect of origins, collecting time, processing, and storage on the CHM color was also analyzed. To overcome the drawback of the traditional identification method, the novel objective color evaluation methods such as spectrocolorimeter and machine vision technology were reviewed, including the application, advantages and disadvantages in Chinese medicine field, and the significance of color sense digitalization was illustrated finally.

Evaluation of performance of the machine vision based on microscope / 国际检验医学杂志

Objective To evaluate performance of the AVE‐766 automated urine sediment analyzer(AVE‐766) based on the ma‐chine vision for detecting erythrocytes(RBCs) ,leukocytes(WBCs) ,epithelial cells(ECs)and CASTs in urine specimen .Methods The within‐run variable coefficients(CVs) ,linearities and carryover rates for RBC ,WBC ,EC ,and CAST in urine specimens detected by using the AVE‐766 were analyzed ,the results of RBC ,WBC ,EC ,and CAST count in urine specimens detected by using AVE‐766 and Fast‐Read102 counting plate(Fast‐Read102) were compared .Results The within‐run CVs for RBC ,WBC ,EC ,and CAST detected by using AVE‐766 and Fast‐Read102 were increased by decreases of concentration of urine sediment .Good linearities (R2 >0 .97 ,P<0 .05) were observed for RBC(in the range of 60 -1 255/μL) ,WBC(in the range of 68 -2 718/μL) ,EC(in the range of 28-296/μL) and CAST(in the range of 5-86/μL) detected by using the AVE‐766 .The carryover rates for RBC ,WBC , EC ,and CAST detected by using AVE‐766 was 0 .9% or less .The values detected by using AVE‐766 were correlated well with those detected by using Fast‐Read102 for RBC ,WBC ,and EC in urine specimens(0 .67< r<0 .75) .However ,for CAST ,the values detected by using AVE‐766 were poorly correlated with those detected by using Fast‐Read102(r=0 .183) .There were statistically significant differences between manual and automated urinalysis for RBC ,WBC ,EC ,and CAST in urine specimens(P<0 .05) .Con‐clusion The AVE‐766 could not take over microscopic examination ,only is suitable for the first screening to detect RBC ,WBC , EC ,and CAST in urine specimen .

Determination methods of content uniformity in preparations of Chinese materia medica / 中草药

In this paper, the essentiality of content uniformity of Chinese materia medica (CMM) is taken as a breakthrough point, the determination and assessment methods which may be used for the content uniformity of CMM are summarized, and the measures respected by author of IR fingerprint and machine vision technology are elaborated, in order to enhance the quality of CMM preparations, strengthen the safety and effectiveness of clinical medicine, and promote the establishment of content uniformity evaluation system suitable for CMM preparations.