CHNSpec Technology （Zhejiang）Co.,Ltd

Application Practice of CHNSpec FS-13 Hyperspectral Camera in Leather Defect Detection

In the leather production and quality control process, subtle defects such as glue leakage and scratches directly affect product grading and market value. Traditional manual visual inspection is easily affected by subjective judgment and fatigue, leading to problems such as low efficiency, inconsistent standards, and frequent missed inspections. Conventional optical testing equipment mostly relies on spatial morphological information and has limited ability to identify optical differences caused by microscopic changes in materials, making it difficult to meet the needs of refined quality inspection. Hyperspectral imaging technology can simultaneously obtain the spatial image and continuous spectral information of the target, with each pixel corresponding to a complete high-resolution spectral curve. Since there are differences in composition and surface structure between leather defect areas and normal areas, the reflection spectra and colorimetric parameters of the two form quantifiable differences in specific bands, providing data support for objective and stable defect identification. I. Experimental Scheme and Equipment Configuration In this case, the CHNSpec FS-13 hyperspectral camera was used to carry out leather defect detection verification. The equipment and parameter settings were tailored to the characteristics of leather samples: Spectral Range: 400–1000nm Spectral Resolution: 2.5nm Working Mode: External push-broom scanning Key Parameters: Exposure time 200μs, motor movement speed 30 mm/s Sample: Leather specimens containing glue leakage defects Detection Goal: Extract and distinguish the spectral and colorimetric characteristics of defect areas and normal areas, and complete defect localization and visual presentation. II. Detection Process and Data Processing 1.Data Acquisition: Scanning the entire leather surface in push-broom mode, simultaneously collecting full-band spectral data and colorimetric parameters such as L, a, b, X, Y, Z for each pixel. Reflectance curves are generated in real-time, forming an integrated "spatial + spectral" dataset. 2.Data Preprocessing and Analysis: Performing calibration and noise reduction on the raw data, focusing on comparing the morphology of reflectance curves between defect areas and normal areas, quantifying colorimetric parameter differences, extracting optical features that can be used to distinguish defects, and establishing a stable identification basis. III. Application Effects and Measured Performance 1.Clear Spectral Feature Differences: Within the 400–1000 nm band, the reflectance curves of the glue leakage area and the normal area show quantifiable waveform differences in peak values, slopes, and characteristic wavelength positions, providing an objective basis for defect determination. 2.Good Discrimination of Colorimetric Parameters: Taking D65/10° standard observation conditions as an example, there are significant differences in L, a, b, and other values between the glue leakage area and the normal area, enabling rapid defect discrimination through numerical thresholds. 3.Precise and Traceable Defect Localization: Combining spatial images with spectral features, the distribution range and boundaries of defects can be accurately locked. Visual detection results and quantified data are outputted, making the detection process reproducible and the results traceable, which facilitates quality control and process optimization.

Application of CHNSpec TH-110 Haze Meter in the Research of Organic Montmorillonite Modified PVB Films

In fields such as automotive safety glass and photovoltaic encapsulation, Polyvinyl Butyral (PVB) films are widely used due to their good light transmittance, bonding properties, and mechanical performance. To further enhance the strength, insulation, and UV shielding capabilities of the films, a university materials team adopted organic montmorillonite to modify PVB. They prepared PVB/organic montmorillonite composite transparent films through in-situ polymerization and used the CHNSpec TH-110 haze meter to complete critical optical performance testing, providing stable and reliable data support for material formula optimization and performance verification. I. Research Background and Testing Requirements Under higher safety standards and complex usage environments, traditional PVB films have room for improvement in mechanical and insulation properties. Nano-montmorillonite can improve the comprehensive performance of polymers at low addition levels, but inorganic fillers are prone to agglomeration, which affects the light transmittance and haze of the film, thereby influencing the visual clarity and user experience of laminated glass. The research team needed to conduct systematic testing on PVB composite films with different modifiers and addition ratios, focusing on: Whether the visible light transmittance meets the relevant specification requirements for laminated glass. The variation patterns of haze to judge the dispersion uniformity of fillers. Differences in the impact of different organically modified montmorillonites on optical parameters. Fast, stable, and repeatable detection of batch samples. II. Application of TH-110 Haze Meter in the Experiment 1. Instrument Selection and Adaptability The research selected the CHNSpec TH-110 haze meter to carry out haze and transmittance testing. The instrument is compatible with multiple standards such as ASTM D1003, ISO 13468, and GB/T 2410, and can simultaneously output measurement results under dual standards, adapting to the data specification requirements for university scientific research and achievement publication. 2. Core Testing Solution Samples: Pure PVB film, PVB/montmorillonite composite film, composite films with montmorillonite modified by different surfactants. Measurement Parameters: Haze, Transmittance. Measurement Method: Open measurement area, adapted for flexible film and sheet samples; utilizing dual measurement apertures of 21mm and 7mm to meet the multi-point testing needs of specimens of different sizes. Operational Process: Place the sample directly after calibration, quickly complete multi-point measurements and take the average value; the data is stable with good repeatability. 3. Key Testing Results and Scientific Research Value The haze of pure PVB film is at a relatively low level, with a uniform internal structure, less light scattering, and stable transmittance performance. After adding montmorillonite/organic montmorillonite, the haze of the film shows an upward trend as the filler content increases, but the haze increase is controllable at low addition levels. The dispersion of organically modified montmorillonite is improved, making the film surface smoother. The haze fluctuation is smaller than that of the unmodified system, confirming that the modification process can enhance the dispersion uniformity of fillers in the PVB matrix. The visible light transmittance of the composite film remains at a high level, meeting the optical index requirements for laminated glass applications, while also possessing a certain degree of UV shielding capability. The TH-110 haze meter, with its 0.01% haze resolution and stable repeatability, helped the team clearly distinguish optical differences between different formulas and contents, providing an objective basis for determining the optimal addition ratio and ensuring that the material maintains qualified transparency and low haze levels while improving mechanical and insulation properties. III. Summary of Application Value Standard Compliance: Supports multiple national and international standards; the detection results can be directly used for academic research and data presentation in papers. Efficient and Stable: No preheating required, fast data output; adapted for batch sample testing in university laboratories, reducing human operational errors. Scenario Adaptability: Dual apertures and an open platform make it convenient to place flexible film samples with flexible measurement. Reliable Data: High resolution and good repeatability can accurately reflect the filler dispersion state and the internal uniformity of the film, supporting material structure-performance correlation analysis. This application shows that the CHNSpec TH-110 haze meter can stably serve the R&D and performance characterization of high-molecular transparent films, providing continuous and reliable optical detection support for formula iteration, process optimization, and performance verification of functional film materials such as PVB-based composite membranes.

Hyperspectral Imaging: A non-destructive detection tool for unlocking the "invisible codes" of Renaissance masterpieces

To commemorate the 500th anniversary of Raphael's death, the Galleria Borghese in Rome utilized reflective Hyperspectral Imaging (HSI) combined with Macro X-ray Fluorescence (MA-XRF) to complete a full-frame, sub-millimeter non-destructive inspection of the Renaissance masterpiece "The Deposition" (Baglioni Entombment). This technology is like giving a famous painting a "non-invasive spectral CT scan," penetrating the pigment layers to reveal underdrawings, traces of modification, and pigment codes hidden for over 500 years, allowing us to understand the master's entire creative process. I. What is Hyperspectral Imaging? Hyperspectral imaging, simply put, is a "two-in-one" of "imaging + spectroscopy." It doesn't just capture a picture; it records the complete spectral information of every pixel from visible light to short-wave infrared (400–1700 nm), turning an ordinary photo into a three-dimensional data cube available for deep analysis. The Visible-Near Infrared-Shortwave Infrared hyperspectral scanner used in this study was specifically designed for cultural relics: it adopts push-broom scanning with extremely high resolution, and the illumination is concentrated only on a narrow area, causing almost no damage to the painting; even when facing curved wooden panels, clear imaging can be guaranteed through optical correction. The research team scanned the entire painting in 8 segments and then precisely stitched them together to obtain ultra-large spectral data, achieving full-frame, zero-dead-angle analysis, completely moving away from the limitations of traditional single-point sampling. II. Seeing Raphael's "Invisible Creations" The greatest capability of hyperspectral imaging is seeing underlying information invisible to the naked eye. With the help of algorithms such as Principal Component Analysis (PCA) and Minimum Noise Fraction (MNF) to process spectral data, "invisible content" within the frame emerges one by one. In the background sky, spectral processing unexpectedly discovered covered early landscapes: originally clearly outlined trees and vegetation were later softened by Raphael to blend into the blue sky, making the space feel more profound; the shapes of the mountains also changed from sharp to rounded. These traces of modification in the middle pigment layers are key evidence difficult to capture with traditional infrared or X-rays, directly restoring the master's composition adjustment process. Even more startling is the underlying sketch. Traditional infrared reflectography can only see carbon-based lines clearly, while hyperspectral imaging—by selecting optimal infrared bands and synthesizing false-color images—clearly presents finer underdrawings: hatching on the male characters' faces and heavy outlines on the Virgin Mary's cheeks and lips, which were previously completely hidden. This proves that Raphael's underdrawings were completed in multiple stages using different materials, making the creative process far more complex than imagined. III. Hyperspectral + XRF Cracks the Red Pigment Code Hyperspectral imaging alone cannot fully determine pigment components; when used in conjunction with MA-XRF, they form a "molecular spectroscopy + elemental analysis" golden duo, precisely cracking the core red code of this painting. Researchers used Spectral Angle Mapping (SAM) to divide the red into three types of spectral characteristics: two types corresponding to red lakes and one type corresponding to vermilion. Then, by cross-referencing the element distribution map from X-ray fluorescence: mercury (Hg) signals only appeared in the vermilion areas, potassium (K) signals confirmed the red lakes, and iron (Fe) was unrelated to the red, excluding iron oxide red. Ultimately, it was confirmed: Raphael used only two red materials, vermilion and red lake, and used three techniques—single-layer thick application, multi-layer glazing, and red lake over vermilion—to create rich layers. Only the core figure, Grifonetto, used "vermilion base + red lake glazing" to highlight his status. This rigorous yet ingenious way of using color was revealed completely for the first time. IV. The Future Core Technology of Cultural Relic Protection This cross-border cooperation between technology and art fully demonstrates the unique value of hyperspectral imaging in cultural relic protection: completely non-destructive, deep penetration, global analysis, and data archivability. It requires no sampling and no damage to the painting to excavate underdrawings, layering, pigments, and restoration traces, becoming a standard tool for museum research, restoration, and digital protection. From invisible underdrawings to covered compositions and then to precise pigment formulas, hyperspectral imaging lets masterpieces "speak" their creative stories. It is not just a cutting-edge technology, but a bridge connecting art history and materials science, protecting and decoding mankind's most precious cultural heritage in the gentlest way.

Precise control of oil color: Application cases of CHNSpec CS-821N spectrophotometer in the sesame processing industry

In the sesame processing industry, mechanized harvesting has become a key means to improve production efficiency. However, seed damage generated during the mechanized harvesting process directly affects the quality characteristics of subsequent sesame oil and sesame paste. Color, as a core indicator of product sensory quality, not only affects consumers' willingness to purchase but also directly reflects the quality of raw materials and the stability of processing technology. Research shows that mechanical harvesting damage accelerates lipid oxidation during sesame storage, leading to a darker, more yellowish, and reddish color in sesame oil, while sesame paste exhibits a lighter color and increased fluctuations in color difference. Traditional manual sensory evaluation methods are heavily influenced by subjective factors, making it difficult to quantify color differences and unable to meet the requirements for quality consistency in large-scale production. In addition, the color of sesame products is closely related to factors such as roasting degree and storage time, requiring precise detection tools to capture subtle color changes. CHNSpec Technology's CS-821N spectrophotometer adopts the principle of spectral color measurement, which can objectively output color parameters such as L, a, and b, transforming visual perception into quantifiable data. This provides a scientific color control solution for sesame processing enterprises, helping them stabilize product quality and optimize production processes. I. Objectively quantifying the subtle color differences of sesame oil In order to objectively and accurately evaluate the color differences of sesame oil, researchers used the CHNSpec Technology CS-821N spectrophotometer. The instrument is based on the colorimetric system recommended by the CIE (International Commission on Illumination). By measuring the spectral data of the sample's reflection or transmission, it calculates the precise value in the color space. In this study, the CS-821N was used to detect the color parameters of all sesame oil samples. The specific operations are as follows: 1.Sample preparation: Sesame oil samples were made from mechanically harvested sesame and manually harvested sesame with different storage periods respectively. 2.Color measurement: Using the CS-821N spectrophotometer under standard light source conditions, the L, a, and b values of each oil sample were measured. Among them: L value represents lightness; a larger value indicates a whiter and brighter color. a value represents red-green degree; a positive value indicates a reddish tint, and a negative value indicates a greenish tint. b value represents yellow-blue degree; a positive value indicates a yellowish tint, and a negative value indicates a bluish tint. Through this method, researchers obtained precise and repeatable color data, avoiding the subjectivity of naked-eye observation and providing a solid foundation for subsequent data analysis and conclusions. II. Color change laws revealed by CS-821N Experimental data clearly revealed the influence of different processing raw materials on the color of sesame oil through the measurement results of the CS-821N: 1.Mechanical harvesting leads to deeper color: Compared with manually harvested sesame, the sesame oil produced from mechanically harvested sesame generally has lower L values and higher a and b values. This indicates that the sesame oil made from mechanically harvested sesame is darker in color and tends toward red and yellow tones. This may be because mechanical harvesting damage leads to the rupture of the sesame seed coat. During the roasting process, the internal sesame kernels can contact heat more directly, resulting in a more sufficient Maillard reaction, thus forming a deeper color. 2.The trend of color change can be quantified: In subsequent accelerated storage experiments, the CS-821N also captured the dynamic changes in the color of sesame oil during the storage process. The L values of all oil samples decreased with the extension of storage time, and the a values increased, manifesting as a further deepening and reddening of the color. The precise values provided by the CS-821N enabled researchers to objectively describe the appearance changes during this oxidation process. III. Application value The application of the CHNSpec CS-821N spectrophotometer in the sesame processing industry has realized the transformation of color evaluation from subjective to objective. Through quantified color data, enterprises can precisely control the quality of raw materials, optimize processing technology, and stabilize the quality of finished products, effectively responding to the quality fluctuation challenges brought by the processing of mechanically harvested sesame. The instrument's characteristics of convenient operation and efficient detection adapt to the rapid detection needs of production lines, while the data traceability function provides strong support for corporate quality management. In the sesame processing industry pursuing quality standardization, the CHNSpec CS-821N spectrophotometer, with its precise detection performance, has become an important tool for enterprises to control the sensory quality of products, helping the industry achieve the dual goals of large-scale production and stable quality.

Application of hyperspectral imaging technology in FPCB surface defect detection

 I. Limitations of traditional visual inspection Flexible Printed Circuit Boards (FPCB) are widely used in fields such as smartphones, flexible displays, and wearable devices due to their good bendability and heat dissipation capabilities. As circuit density continues to increase, the types of surface defects are becoming increasingly complex, with common defects including short circuits, open circuits, protrusions, white spots, black spots, and broken holes. In traditional detection methods, template matching based on RGB images is widely used. This method locates abnormal areas by comparing a standard image with the image under test. However, these methods are sensitive to lighting conditions; when the light distribution is uneven, it is easy to produce false detections or missed detections. In addition, some defects are morphologically similar to normal circuit structures, making it difficult to distinguish them accurately relying solely on visible light images. II. Construction of the hyperspectral imaging system To improve the stability of detection, this study built a hyperspectral microscopic imaging system. The system consists of a hyperspectral camera, a microscope, and acquisition software. Among them, the hyperspectral camera adopts the FS-23 model from CHNSpec, which features a spectral range of 400–1000nm and a spectral resolution of 2.5nm. The camera uses a line-scanning method for imaging, and the raw data contains 1200 bands. To facilitate processing, every four adjacent bands were merged into one in the study, finally obtaining a data structure of 300 bands. The size of a single hyperspectral image is 1920 × 960 pixels × 300 bands, covering the complete spectral information of the copper conductor and the polyimide substrate. The advantage of hyperspectral imaging lies in its ability to obtain a continuous spectral curve for each pixel. The study found that there are significant differences in the spectral response of copper and polyimide in the 500–750nm wavelength range, which provides a reliable basis for subsequent image segmentation and material identification. III. Spectral information-driven detection method The detection framework proposed in this study consists of two sub-networks: FPCB-LocNet for defect localization and FPCB-ClaNet for defect classification. In the localization stage, FPCB-LocNet utilizes multi-scale 3D convolution kernels to extract features from both spatial and spectral dimensions simultaneously. Two different sizes of convolution kernels are used in the network to focus on local spatial structures and spectral features respectively, and features of different scales are fused through a residual structure. This design allows the network to capture fine spatial textures and continuous spectral changes at the same time, achieving pixel-level segmentation of copper and polyimide. After segmentation is completed, abnormal areas are located through template matching. In the classification stage, considering the limited number of hyperspectral samples, the network adopts a transfer learning strategy, first pre-training on the FPCB RGB image dataset and then fine-tuning on pseudo-color images. Aiming at the problem of unbalanced sample numbers for different defect categories, category-balanced sampling and weight decay strategies are introduced in the network to enable the model to focus more on defect types with fewer samples. At the same time, the SE attention mechanism is embedded to enhance the network's focus on key features. IV. Experimental results and application value In terms of image segmentation, FPCB-LocNet performs better than traditional segmentation methods such as entropy method, watershed algorithm, and Otsu when processing images with uneven lighting, with a segmentation accuracy reaching 97.86%. In the classification task, the comprehensive classification accuracy of FPCB-ClaNet for six common types of defects is 97.84%. Ablation experiments verified the actual contribution of each module: data augmentation improved classification accuracy, category-balanced sampling and weight decay effectively improved the recognition effect of tail categories, and the SE attention mechanism brought a stable improvement in classification performance while adding a small number of parameters. The visualization results of Grad-CAM heatmaps show that the model's areas of concern are highly consistent with the actual defect locations. This study combines hyperspectral imaging with deep learning to build a complete processing chain from data acquisition, image segmentation, and defect localization to defect classification. This method can stably complete the identification task of FPCB surface defects without relying on specific lighting conditions, providing a feasible technical path for the manufacturing quality management of high-density flexible circuit boards. Product Recommendation: FigSpec FS-23 Imaging Hyperspectral Camera Image Resolution: 1920*1920 Spectral Range: 400-1000nm Spectral Resolution (FWHM): 2.5nm Number of Spectral Channels: 1200

The National Standard for the Printing Industry Primarily Drafted by CHNSpec Has Been Officially Approved

Recently, the national standard Printing Technology—Color and Transparency of Four-Color Printing Inks—Part 2: Coldset Web Offset Printing (Plan No.: 20232426-T-421), led and primarily drafted by CHNSpec, has been officially approved and released. This standard is administered by the National Printing Standardization Technical Committee (TC170) and supervised by the National Press and Publication Administration (National Copyright Administration). Its implementation will inject critical momentum into the standardized and internationalized development of color quality control in China’s printing industry. As a technical specification that is identical to the international standard ISO 2846-2:2007, this standard precisely focuses on the core indicators of color and transparency of four-color printing inks in coldset web offset printing scenarios. It successfully fills the gap in China’s seamless alignment between technical requirements in this segmented field and advanced international standards, helping elevate the industry’s technical level to international benchmarks. Throughout the entire standard development process, CHNSpec fully leveraged its technical expertise and accumulated strengths in spectral measurement and colorimetric calculation, serving as a core technical support contributor. Drawing on many years of in-depth practice in the field of color measurement, the team deeply participated in the optimization of test methods for color uniformity and transparency tailored to the characteristics of coldset web offset inks. In particular, in key aspects such as measurement accuracy control and data repeatability verification, CHNSpec provided a large amount of detailed and reliable practical data, laying a solid foundation for the scientific rigor and practicality of the standard. CHNSpec worked closely with Shandong Taibao Information Technology Group Co., Ltd., Anhui Xinhua Printing Co., Ltd., Xi’an University of Technology, and other drafting organizations. Through multiple rounds of technical discussions, laboratory validation, and text revisions, all parties jointly promoted the continuous improvement of the standard content, ensuring that it not only meets real-world industry application needs but also maintains strict technical authority.

Overwhelming Popularity! CHNSpec Wins Over the Entire Venue with Hardcore Technology on the First Day of the ChinaCoat Exhibition

Shortly after the ChinaCoat exhibition opened, the CHNSpec booth was already “surrounded” by crowds! The sounds of inquiries and explanations intertwined into the liveliest melody, instantly pushing the first-day popularity to its peak. CHNSpec proved its brand strength with genuine, tangible popularity.   In the core exhibition area, the AI large-model coating color-matching system was packed with visitors eager to experience it. By simply importing a sample color card, the system could generate an accurate formula within seconds, improving efficiency by 80% compared with traditional methods. While operating the system, staff members explained its features, and their notebooks quickly filled with customer notes such as “automotive paint adaptation requirements” and “on-site trial after the exhibition.” The seats in the discussion area were never empty.   The adjacent multi-angle spectrophotometer exhibition area was even more bustling. As a dedicated color measurement solution for metallic and pearlescent paints, it leverages 12-angle measurement technology to solve color deviation issues caused by varying light angles in such special coatings. As soon as it was unveiled, it was immediately surrounded by customers from the coatings industry. “Batch color differences in pearlescent paint have always been our pain point. This device can accurately capture color difference values from different viewing angles—it’s truly practical!” said a technical director from a coatings factory while quickly taking notes during the demonstration, and he scheduled an in-depth technical exchange for the next day on the spot.   The DS-36D series spectrophotometer was particularly eye-catching. During the live demonstration, when the engineer announced the technical parameter “repeatability accuracy up to dE*ab ≤ 0.005,” it immediately sparked a wave of amazement. After repeatedly comparing the data, a customer from the automotive parts industry gave a thumbs-up and said, “This is exactly the kind of precision equipment we need to solve our batch color difference problems,” and promptly left a detailed requirement list for further in-depth collaboration.   From the first light of morning to the fall of dusk, the wave of inquiries at the CHNSpec booth never slowed down. Seats at the consultation desk were constantly “in short supply.” As soon as technical engineers finished answering parameter questions for one customer on the left, new visitors on the right were already waiting with samples in hand. Promotional material racks were emptied and replenished again and again, while registration forms grew thicker page by page. Some long-term clients came specifically with cooperation plans, while new partners attracted by the brand’s reputation stopped for in-depth discussions. Voices of consultation from different industries intertwined, and every business card exchanged carried potential collaboration opportunities. The busy yet vibrant scene was truly the most beautiful landscape of the exhibition.  

Good News | CHNSpec Wins the First Prize of the China General Chamber of Commerce Technology Invention Award

Recently, the China General Chamber of Commerce officially released the announcement of the selection results for the “2025 China General Chamber of Commerce Science and Technology Awards.” With its technological innovation achievement “Spectrophotometer Based on a Hyperspectral Imaging System,” CHNSpec successfully won the First Prize of the Technology Invention Award, demonstrating the company’s solid technical strength and industry-leading position in the field of color measurement technology. As an important award in China’s commercial science and technology sector, the China General Chamber of Commerce Science and Technology Award features a rigorous and standardized evaluation process. Candidates must be recommended by local chambers of commerce, industry associations, research institutions, and higher education institutions, and then pass multiple stringent stages including preliminary evaluation, expert review, evaluation committee approval, and public announcement. Award-winning projects represent a high level of technological innovation and application value in their respective fields. In this selection, a total of 143 Technology Invention Awards were granted, with only 41 First Prizes. CHNSpec’s award-winning project stood out among numerous entries thanks to its breakthrough technological innovation. Since its establishment, CHNSpec has consistently focused on the R&D and innovation of color measurement and optical detection technologies. The company has built a research and development team composed of senior industry experts and technical backbones, adhered to a market-demand-oriented approach, and continuously invested in tackling core technologies. This award is a high-level recognition of the company’s long-term commitment to scientific and technological innovation, and an important achievement of its development philosophy of “building the enterprise through technology and driving growth through innovation.” Looking ahead, CHNSpec will continue to deepen its efforts in core technology research and development, increase investment in scientific research, and continuously optimize product performance and application solutions. Through more high-quality technological innovation achievements, the company aims to empower the development of various industries and contribute greater strength to the advancement of China’s commercial science and technology and industrial upgrading.